-------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>

. do "C:\Users\brdbl\AppData\Local\Temp\STD5ca8_000000.tmp"

. clear

. use "ReplicationData_ISQ_Promises.dta"

. 
. *Table 1
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region i.year lag_log_gdp lag_latency_pilot lag_nwcapability log_distance log_distance_us MID_movingavg
> _notinitiator MID_movingavg_aggressor lag_democracy lag_log_trade lag_rivalry_thompson lag_rivalry_shared lag_troops adv_signal_las
> t3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -981.30353  
Iteration 1:   log pseudolikelihood = -803.87243  
Iteration 2:   log pseudolikelihood =  -763.0112  
Iteration 3:   log pseudolikelihood =  -762.3389  
Iteration 4:   log pseudolikelihood = -762.30131  
Iteration 5:   log pseudolikelihood = -762.29377  
Iteration 6:   log pseudolikelihood = -762.29215  
Iteration 7:   log pseudolikelihood = -762.29178  
Iteration 8:   log pseudolikelihood = -762.29169  
Iteration 9:   log pseudolikelihood = -762.29167  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -869.03507  (not concave)
Iteration 1:   log pseudolikelihood = -771.73712  
Iteration 2:   log pseudolikelihood =  -749.3046  
Iteration 3:   log pseudolikelihood = -747.20667  
Iteration 4:   log pseudolikelihood = -747.13704  
Iteration 5:   log pseudolikelihood = -747.13702  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(31)     =          .
Dispersion           = mean                     Prob > chi2       =          .
Log pseudolikelihood = -747.13702               Pseudo R2         =     0.1963

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4083686   .3153442    -1.29   0.195    -1.026432    .2096947
                        5  |   2.913905   .5013611     5.81   0.000     1.931256    3.896555
                           |
                      year |
                     1952  |  -.9824788   1.324775    -0.74   0.458    -3.578991    1.614033
                     1953  |  -1.548802   1.103698    -1.40   0.161     -3.71201     .614406
                     1954  |  -.9840548   .6621661    -1.49   0.137    -2.281877     .313767
                     1955  |  -.5563283   .9908576    -0.56   0.574    -2.498373    1.385717
                     1956  |  -19.06523   .7199295   -26.48   0.000    -20.47626   -17.65419
                     1957  |  -.6656381   1.163515    -0.57   0.567    -2.946085    1.614809
                     1958  |  -.7270197   .5153327    -1.41   0.158    -1.737053    .2830139
                     1959  |  -1.902391   1.284082    -1.48   0.138    -4.419146    .6143633
                     1960  |  -.9516841     .49007    -1.94   0.052    -1.912204    .0088354
                     1961  |  -.6322197   .8570508    -0.74   0.461    -2.312008    1.047569
                     1962  |   .0844091   .8560314     0.10   0.921    -1.593382      1.7622
                     1963  |  -1.153204   1.072149    -1.08   0.282    -3.254577      .94817
                     1964  |  -1.216864   .7886865    -1.54   0.123    -2.762661    .3289333
                     1965  |   -.553257   .6129063    -0.90   0.367    -1.754531    .6480173
                     1966  |  -.4685132   .5573276    -0.84   0.401    -1.560855    .6238288
                     1967  |  -.6753046   .8114082    -0.83   0.405    -2.265636    .9150263
                     1968  |  -.6604774   1.029035    -0.64   0.521     -2.67735    1.356395
                     1969  |  -.6138973   .8988461    -0.68   0.495    -2.375603    1.147809
                     1970  |  -.2855183   .9095076    -0.31   0.754    -2.068121    1.497084
                     1971  |   .1612328   .7550857     0.21   0.831    -1.318708    1.641174
                     1972  |  -.0060057   .7777602    -0.01   0.994    -1.530388    1.518376
                     1973  |  -.0785163   .9232095    -0.09   0.932    -1.887974    1.730941
                     1974  |   .2582758   .8671855     0.30   0.766    -1.441377    1.957928
                     1975  |    .552796   .7898949     0.70   0.484    -.9953695    2.100962
                     1976  |    .628174   .8121841     0.77   0.439    -.9636775    2.220026
                     1977  |   .1125232   .9829482     0.11   0.909     -1.81402    2.039066
                     1978  |  -.8246554   .8177122    -1.01   0.313    -2.427342    .7780309
                     1979  |   .8711226   .9471574     0.92   0.358    -.9852718    2.727517
                     1980  |   .5574068   .9645959     0.58   0.563    -1.333166     2.44798
                     1981  |   .3880184   .9793073     0.40   0.692    -1.531389    2.307425
                     1982  |  -.5539537   .9384164    -0.59   0.555    -2.393216    1.285309
                     1983  |   .4427063   .8957166     0.49   0.621    -1.312866    2.198279
                     1984  |  -.2145657   1.031067    -0.21   0.835     -2.23542    1.806289
                     1985  |   .3768709   .8935951     0.42   0.673    -1.374543    2.128285
                     1986  |  -.2502265   .8697107    -0.29   0.774    -1.954828    1.454375
                     1987  |   -.457575   1.004633    -0.46   0.649     -2.42662     1.51147
                     1988  |  -.0127813   .9787473    -0.01   0.990    -1.931091    1.905528
                     1989  |    .371209   .9184177     0.40   0.686    -1.428857    2.171275
                     1990  |  -.3689633   .9922128    -0.37   0.710    -2.313665    1.575738
                     1991  |   .1023933   1.100164     0.09   0.926    -2.053888    2.258674
                     1992  |  -.0933642   .6823908    -0.14   0.891    -1.430826    1.244097
                     1993  |   .4448752   .7768821     0.57   0.567    -1.077786    1.967536
                     1994  |   .0127429   .9028346     0.01   0.989     -1.75678    1.782266
                     1995  |  -.2710753   .9882622    -0.27   0.784    -2.208034    1.665883
                     1996  |   .5741263   .9239786     0.62   0.534    -1.236839    2.385091
                     1997  |  -1.069597   1.076262    -0.99   0.320    -3.179031    1.039837
                     1998  |  -.0265447    .943125    -0.03   0.978    -1.875036    1.821946
                     1999  |  -.4010592   .9835279    -0.41   0.683    -2.328738     1.52662
                     2000  |  -1.073894   1.007128    -1.07   0.286    -3.047828    .9000408
                     2001  |   .2830796   .7828439     0.36   0.718    -1.251266    1.817425
                     2002  |  -.0930866   .7611508    -0.12   0.903    -1.584915    1.398742
                     2003  |   .4478529   .7446568     0.60   0.548    -1.011648    1.907354
                     2004  |  -1.467665   1.165802    -1.26   0.208    -3.752595    .8172654
                     2005  |  -.0033219   1.158958    -0.00   0.998    -2.274838    2.268194
                     2006  |  -.4798788   .9852492    -0.49   0.626    -2.410932    1.451174
                     2007  |  -.0969605   .9775302    -0.10   0.921    -2.012885    1.818963
                     2008  |  -.3592637   .8588145    -0.42   0.676    -2.042509    1.323982
                     2009  |   .9332156   .8965415     1.04   0.298    -.8239735    2.690405
                     2010  |   .3805745   .8635059     0.44   0.659    -1.311866    2.073015
                           |
               lag_log_gdp |   .5788424    .233588     2.48   0.013     .1210184    1.036666
         lag_latency_pilot |   .9110852    .172427     5.28   0.000     .5731346    1.249036
          lag_nwcapability |   1.031379   .3232818     3.19   0.001     .3977582       1.665
              log_distance |  -.3579596   .1707685    -2.10   0.036    -.6926596   -.0232596
           log_distance_us |  -.0072188   .6128537    -0.01   0.991     -1.20839    1.193952
MID_movingavg_notinitiator |   .0153483   .0446652     0.34   0.731    -.0721939    .1028905
   MID_movingavg_aggressor |   .0250232   .0357071     0.70   0.483    -.0449614    .0950079
             lag_democracy |   .0473638   .3695777     0.13   0.898    -.6769952    .7717227
             lag_log_trade |  -.5023581   .2227796    -2.25   0.024     -.938998   -.0657182
      lag_rivalry_thompson |   .4769841   .1269614     3.76   0.000     .2281443    .7258238
        lag_rivalry_shared |  -.1792004   .2437977    -0.74   0.462    -.6570351    .2986343
                lag_troops |   -.003708   .0026006    -1.43   0.154    -.0088051    .0013891
          adv_signal_last3 |   .1562168    .096487     1.62   0.105    -.0328942    .3453279
                     _cons |  -3.640087   5.665092    -0.64   0.521    -14.74346    7.463289
---------------------------+----------------------------------------------------------------
                  /lnalpha |   -.545055   .5942053                     -1.709676    .6195659
---------------------------+----------------------------------------------------------------
                     alpha |   .5798099   .3445261                      .1809244    1.858121
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.ccode postcw t t2 t3 log_cas us_gdp_growth lag_latency_pilot lag_nwcapability MID_movingavg_notinitiato
> r MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy lag_troops adv_signal_last3   if sample_cow
> ==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1583.7495  
Iteration 1:   log pseudolikelihood = -1030.6836  
Iteration 2:   log pseudolikelihood = -884.89009  
Iteration 3:   log pseudolikelihood = -785.99956  
Iteration 4:   log pseudolikelihood = -784.31471  
Iteration 5:   log pseudolikelihood = -784.29586  
Iteration 6:   log pseudolikelihood = -784.29235  
Iteration 7:   log pseudolikelihood = -784.29177  
Iteration 8:   log pseudolikelihood = -784.29164  
Iteration 9:   log pseudolikelihood = -784.29161  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -981.85166  
Iteration 1:   log pseudolikelihood = -930.64939  
Iteration 2:   log pseudolikelihood = -930.56498  
Iteration 3:   log pseudolikelihood = -930.56497  

Fitting full model:

Iteration 0:   log pseudolikelihood = -930.56497  (not concave)
Iteration 1:   log pseudolikelihood = -776.93785  
Iteration 2:   log pseudolikelihood = -756.27968  
Iteration 3:   log pseudolikelihood = -753.57081  
Iteration 4:   log pseudolikelihood =  -753.4505  
Iteration 5:   log pseudolikelihood = -753.42393  
Iteration 6:   log pseudolikelihood = -753.41817  
Iteration 7:   log pseudolikelihood = -753.41723  
Iteration 8:   log pseudolikelihood =   -753.417  
Iteration 9:   log pseudolikelihood = -753.41695  
Iteration 10:  log pseudolikelihood = -753.41694  

Negative binomial regression                    Number of obs     =      1,248
                                                Wald chi2(27)     =          .
Dispersion           = mean                     Prob > chi2       =          .
Log pseudolikelihood = -753.41694               Pseudo R2         =     0.1904

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                     ccode |
                      210  |  -.2017009   .2855276    -0.71   0.480    -.7613247    .3579229
                      211  |  -.2844622   .3532263    -0.81   0.421    -.9767731    .4078486
                      212  |   -15.0013   1.097895   -13.66   0.000    -17.15314   -12.84947
                      220  |    .310817   .1265531     2.46   0.014     .0627775    .5588565
                      230  |  -1.252228   .4180002    -3.00   0.003    -2.071493   -.4329626
                      235  |  -.1851732   .3864364    -0.48   0.632    -.9425746    .5722281
                      255  |   .3889728   1.042474     0.37   0.709    -1.654239    2.432184
                      290  |   2.026229   .4441415     4.56   0.000     1.155728    2.896731
                      310  |  -.1712424   .4474478    -0.38   0.702    -1.048224    .7057393
                      316  |   .5022724   .4487303     1.12   0.263    -.3772228    1.381768
                      317  |  -14.95713   1.103156   -13.56   0.000    -17.11928   -12.79499
                      325  |  -.0661947   .2394905    -0.28   0.782    -.5355875    .4031981
                      339  |  -15.17628    1.11607   -13.60   0.000    -17.36374   -12.98882
                      344  |  -15.08978   1.104404   -13.66   0.000    -17.25438   -12.92519
                      349  |  -15.02278   1.110173   -13.53   0.000    -17.19867   -12.84688
                      350  |   1.032611    .470622     2.19   0.028     .1102088    1.955013
                      355  |    1.42197   .4387701     3.24   0.001      .561996    2.281943
                      360  |   .3381343   .4333638     0.78   0.435    -.5112432    1.187512
                      366  |  -15.01122   1.108419   -13.54   0.000    -17.18368   -12.83876
                      367  |   1.088095   .4494498     2.42   0.015     .2071892       1.969
                      368  |   1.477863   .4447584     3.32   0.001     .6061525    2.349573
                      385  |  -.7765746   .3687617    -2.11   0.035    -1.499334   -.0538149
                      390  |  -.1698745   .4146748    -0.41   0.682    -.9826221    .6428732
                      395  |  -1.774165   .3867954    -4.59   0.000     -2.53227   -1.016061
                      640  |   .7498836   .3703003     2.03   0.043     .0241083    1.475659
                      713  |   2.107043   .4551702     4.63   0.000     1.214926    2.999161
                      732  |   2.112963   .4619275     4.57   0.000     1.207602    3.018324
                      740  |   2.722652   .3271159     8.32   0.000     2.081517    3.363788
                      770  |   .6913201   .2228748     3.10   0.002     .2544934    1.128147
                      840  |   1.794467   .4183916     4.29   0.000     .9744341    2.614499
                      900  |    1.64594   .4590723     3.59   0.000     .7461745    2.545705
                      920  |   1.903367   .4085147     4.66   0.000     1.102693    2.704041
                           |
                    postcw |   .4778657   .4918073     0.97   0.331    -.4860589     1.44179
                         t |  -.2134269   .0860723    -2.48   0.013    -.3821255   -.0447283
                        t2 |   .0041656   .0024105     1.73   0.084    -.0005589    .0088902
                        t3 |  -.0000293   .0000234    -1.25   0.211    -.0000753    .0000166
                   log_cas |   .0590079   .0295235     2.00   0.046      .001143    .1168728
             us_gdp_growth |  -.0495985   .0246653    -2.01   0.044    -.0979416   -.0012555
         lag_latency_pilot |   .5998536   .2942404     2.04   0.041     .0231529    1.176554
          lag_nwcapability |   .9396296   .4347982     2.16   0.031     .0874408    1.791818
MID_movingavg_notinitiator |   .0240234    .042997     0.56   0.576    -.0602491    .1082959
   MID_movingavg_aggressor |   .0337713   .0314135     1.08   0.282     -.027798    .0953407
        lag_adversary_cinc |   .0235651   .0182834     1.29   0.197    -.0122697    .0593998
               lag_us_cinc |  -.2894697   .0671016    -4.31   0.000    -.4209863    -.157953
          provocation_new3 |   .1692272   .1674694     1.01   0.312    -.1590068    .4974612
             lag_democracy |   .1562263    .287696     0.54   0.587    -.4076474    .7201001
                lag_troops |  -.0051621   .0075054    -0.69   0.492    -.0198725    .0095483
          adv_signal_last3 |   .0567549   .0871415     0.65   0.515    -.1140392     .227549
                     _cons |   4.973606   2.006783     2.48   0.013     1.040383    8.906829
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.2923835    .292617                     -.8659023    .2811354
---------------------------+----------------------------------------------------------------
                     alpha |   .7464822   .2184334                      .4206718    1.324633
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson lag_idealpoint_us_diff lag_rivalry_shared adv_signal_last3 lag_troops if sample_cow==1, vce(clust
> er id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -986.45289  
Iteration 1:   log pseudolikelihood =  -793.5122  
Iteration 2:   log pseudolikelihood = -722.43763  
Iteration 3:   log pseudolikelihood = -721.36377  
Iteration 4:   log pseudolikelihood = -721.35988  
Iteration 5:   log pseudolikelihood = -721.35988  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood =  -889.8324  
Iteration 1:   log pseudolikelihood = -840.81197  
Iteration 2:   log pseudolikelihood = -840.78547  
Iteration 3:   log pseudolikelihood = -840.78547  

Fitting full model:

Iteration 0:   log pseudolikelihood = -766.64038  
Iteration 1:   log pseudolikelihood = -710.60052  
Iteration 2:   log pseudolikelihood = -692.48078  
Iteration 3:   log pseudolikelihood = -690.25217  
Iteration 4:   log pseudolikelihood = -690.24807  
Iteration 5:   log pseudolikelihood = -690.24807  

Negative binomial regression                    Number of obs     =      1,126
                                                Wald chi2(25)     =   13792.84
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -690.24807               Pseudo R2         =     0.1790

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.2374257   .2964462    -0.80   0.423    -.8184496    .3435983
                        5  |   3.524758   .5045305     6.99   0.000     2.535896     4.51362
                           |
                    postcw |   .4684991   .4683017     1.00   0.317    -.4493553    1.386354
                         t |   -.380767   .1531129    -2.49   0.013    -.6808628   -.0806713
                        t2 |   .0094952   .0041261     2.30   0.021     .0014083    .0175822
                        t3 |  -.0000799   .0000369    -2.17   0.030    -.0001521   -7.63e-06
                   log_cas |   .1033117   .0345292     2.99   0.003     .0356357    .1709877
             us_gdp_growth |  -.0713186   .0264655    -2.69   0.007    -.1231899   -.0194472
               lag_log_gdp |   .6412281   .1984438     3.23   0.001     .2522854    1.030171
         lag_latency_pilot |   1.148921   .2087864     5.50   0.000     .7397067    1.558134
          lag_nwcapability |   1.218395   .2895124     4.21   0.000     .6509613    1.785829
              log_distance |  -.6275539   .1692417    -3.71   0.000    -.9592616   -.2958461
           log_distance_us |   .2682667   .8132854     0.33   0.742    -1.325743    1.862277
MID_movingavg_notinitiator |  -.0139507   .0475819    -0.29   0.769    -.1072095     .079308
   MID_movingavg_aggressor |  -.0020404   .0307243    -0.07   0.947    -.0622589    .0581781
        lag_adversary_cinc |  -.0264286   .0263638    -1.00   0.316    -.0781007    .0252435
               lag_us_cinc |  -.3723055   .1114589    -3.34   0.001    -.5907609   -.1538501
          provocation_new3 |   .1294787   .2067433     0.63   0.531    -.2757308    .5346882
             lag_democracy |   .0446995   .3484435     0.13   0.898    -.6382373    .7276363
             lag_log_trade |  -.6055181   .1765988    -3.43   0.001    -.9516454   -.2593907
      lag_rivalry_thompson |   .6202689    .128562     4.82   0.000      .368292    .8722457
    lag_idealpoint_us_diff |   .3712224   .1713929     2.17   0.030     .0352984    .7071463
        lag_rivalry_shared |  -.3732635   .2456641    -1.52   0.129    -.8547562    .1082293
          adv_signal_last3 |   .1817138   .0546423     3.33   0.001     .0746169    .2888108
                lag_troops |  -.0092631   .0017992    -5.15   0.000    -.0127894   -.0057368
                     _cons |   6.156701   9.029232     0.68   0.495    -11.54027    23.85367
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1975454   .2758743                     -.7382491    .3431583
---------------------------+----------------------------------------------------------------
                     alpha |   .8207429   .2264219                        .47795    1.409392
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow_americas==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -2109.6402  
Iteration 1:   log pseudolikelihood = -1497.7556  
Iteration 2:   log pseudolikelihood = -1440.5121  
Iteration 3:   log pseudolikelihood =   -927.749  
Iteration 4:   log pseudolikelihood = -910.68185  
Iteration 5:   log pseudolikelihood =  -910.2441  
Iteration 6:   log pseudolikelihood = -910.24344  
Iteration 7:   log pseudolikelihood = -910.24344  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -1358.4316  (not concave)
Iteration 1:   log pseudolikelihood = -1202.5605  
Iteration 2:   log pseudolikelihood =  -1202.541  
Iteration 3:   log pseudolikelihood =  -1202.541  

Fitting full model:

Iteration 0:   log pseudolikelihood = -1110.2806  (not concave)
Iteration 1:   log pseudolikelihood = -953.04861  
Iteration 2:   log pseudolikelihood = -886.60481  
Iteration 3:   log pseudolikelihood = -870.81556  
Iteration 4:   log pseudolikelihood =  -868.2189  
Iteration 5:   log pseudolikelihood = -868.16143  
Iteration 6:   log pseudolikelihood = -868.16131  
Iteration 7:   log pseudolikelihood = -868.16131  

Negative binomial regression                    Number of obs     =      2,867
                                                Wald chi2(25)     =    2161.27
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -868.16131               Pseudo R2         =     0.2781

                                                  (Std. Err. adjusted for 67 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        2  |   3.192949   .7215282     4.43   0.000      1.77878    4.607119
                        4  |   3.370311    .813034     4.15   0.000     1.776793    4.963828
                        5  |   7.181668   .8162144     8.80   0.000     5.581917    8.781419
                           |
                    postcw |  -.0960698   .5198662    -0.18   0.853    -1.114989    .9228492
                         t |  -.2432249   .0730115    -3.33   0.001    -.3863248    -.100125
                        t2 |   .0052067   .0019855     2.62   0.009     .0013151    .0090982
                        t3 |  -.0000375   .0000195    -1.92   0.055    -.0000758    7.42e-07
                   log_cas |   .0598929   .0276232     2.17   0.030     .0057525    .1140334
             us_gdp_growth |  -.0566296   .0221212    -2.56   0.010    -.0999864   -.0132728
               lag_log_gdp |   .2195278   .1270533     1.73   0.084    -.0294921    .4685477
         lag_latency_pilot |   .8162791   .1584219     5.15   0.000     .5057779     1.12678
          lag_nwcapability |   .7369231   .3653297     2.02   0.044     .0208899    1.452956
              log_distance |  -.2109547   .1702453    -1.24   0.215    -.5446294      .12272
           log_distance_us |  -1.819335   .3566939    -5.10   0.000    -2.518442   -1.120228
MID_movingavg_notinitiator |   .0217618   .0398007     0.55   0.585    -.0562462    .0997698
   MID_movingavg_aggressor |   .0120974   .0318364     0.38   0.704    -.0503008    .0744956
        lag_adversary_cinc |  -.0216681   .0222354    -0.97   0.330    -.0652487    .0219125
               lag_us_cinc |  -.2608912   .0687598    -3.79   0.000    -.3956579   -.1261246
          provocation_new3 |    .212151    .159468     1.33   0.183    -.1004006    .5247025
             lag_democracy |   .1444514   .2881291     0.50   0.616    -.4202712     .709174
             lag_log_trade |  -.1302579   .0546613    -2.38   0.017    -.2373921   -.0231238
      lag_rivalry_thompson |   .8260713   .2072135     3.99   0.000     .4199403    1.232202
        lag_rivalry_shared |  -.2897375   .2074735    -1.40   0.163    -.6963781    .1169031
                lag_troops |  -.0056794   .0036997    -1.54   0.125    -.0129306    .0015718
          adv_signal_last3 |   .2089415   .0818453     2.55   0.011     .0485277    .3693553
                     _cons |   16.67653   3.515623     4.74   0.000     9.786036    23.56702
---------------------------+----------------------------------------------------------------
                  /lnalpha |   .0229496   .3371687                     -.6378889    .6837882
---------------------------+----------------------------------------------------------------
                     alpha |   1.023215   .3449961                      .5284068    1.981369
--------------------------------------------------------------------------------------------

. 
. *Table 2
. ologit us_intervene_amer i.ccode t t2 t3 postcw log_cas us_gdp_growth if sample_cow==1, vce(cluster id)

Iteration 0:   log pseudolikelihood = -425.80231  
Iteration 1:   log pseudolikelihood =  -374.9002  
Iteration 2:   log pseudolikelihood = -347.84043  
Iteration 3:   log pseudolikelihood = -345.66491  
Iteration 4:   log pseudolikelihood = -345.26608  
Iteration 5:   log pseudolikelihood = -345.19825  
Iteration 6:   log pseudolikelihood = -345.18255  
Iteration 7:   log pseudolikelihood = -345.17879  
Iteration 8:   log pseudolikelihood = -345.17803  
Iteration 9:   log pseudolikelihood = -345.17791  
Iteration 10:  log pseudolikelihood = -345.17788  
Iteration 11:  log pseudolikelihood = -345.17787  

Ordered logistic regression                     Number of obs     =      1,248
                                                Wald chi2(31)     =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -345.17787               Pseudo R2         =     0.1893

                                         (Std. Err. adjusted for 33 clusters in id)
-----------------------------------------------------------------------------------
                  |               Robust
us_intervene_amer |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
            ccode |
             210  |  -.6324226   .0253058   -24.99   0.000    -.6820211   -.5828241
             211  |  -1.405289   .0407177   -34.51   0.000    -1.485094   -1.325483
             212  |   -2.55291   .0499327   -51.13   0.000    -2.650777   -2.455044
             220  |  -.2876398      .0134   -21.47   0.000    -.3139034   -.2613762
             230  |  -.5027686   .1319782    -3.81   0.000    -.7614412   -.2440961
             235  |  -1.092431   .0365675   -29.87   0.000    -1.164102    -1.02076
             255  |  -.2560146    .021758   -11.77   0.000    -.2986595   -.2133698
             290  |   -1.04152   .2717691    -3.83   0.000    -1.574177   -.5088618
             310  |   -1.04152   .2717691    -3.83   0.000    -1.574177   -.5088618
             316  |   -1.04152   .2717691    -3.83   0.000    -1.574177   -.5088618
             317  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             325  |  -1.086828   .0343418   -31.65   0.000    -1.154137    -1.01952
             339  |  -17.19768   1.150479   -14.95   0.000    -19.45258   -14.94279
             344  |  -17.19768   1.150479   -14.95   0.000    -19.45258   -14.94279
             349  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             350  |  -1.084437   .0333177   -32.55   0.000    -1.149739   -1.019136
             355  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             360  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             366  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             367  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             368  |  -16.97613   1.089097   -15.59   0.000    -19.11072   -14.84154
             385  |  -1.081946   .0331787   -32.61   0.000    -1.146975   -1.016917
             390  |  -1.086886   .0347502   -31.28   0.000    -1.154995   -1.018777
             395  |   -2.55291   .0499327   -51.13   0.000    -2.650777   -2.455044
             640  |  -.1431624   .0087294   -16.40   0.000    -.1602717   -.1260532
             713  |   .6526158   .3237418     2.02   0.044     .0180934    1.287138
             732  |   .8599826   .0546029    15.75   0.000     .7529629    .9670024
             740  |  -.8792445   .0380671   -23.10   0.000    -.9538547   -.8046344
             770  |  -.1475208    .041303    -3.57   0.000    -.2284731   -.0665685
             840  |  -16.91799    1.01798   -16.62   0.000     -18.9132   -14.92279
             900  |  -1.888804   .0598949   -31.54   0.000    -2.006196   -1.771412
             920  |   -16.3535   1.035383   -15.79   0.000    -18.38281   -14.32419
                  |
                t |   -.156759   .1196178    -1.31   0.190    -.3912057    .0776876
               t2 |   .0037618   .0040142     0.94   0.349    -.0041059    .0116296
               t3 |  -.0000234   .0000358    -0.65   0.514    -.0000936    .0000469
           postcw |   1.142411   .3325484     3.44   0.001      .490628    1.794194
          log_cas |  -.2851107    .105759    -2.70   0.007    -.4923946   -.0778269
    us_gdp_growth |  -.0213668   .0341553    -0.63   0.532    -.0883101    .0455764
------------------+----------------------------------------------------------------
            /cut1 |  -.0508951   .7871017                     -1.593586    1.491796
            /cut2 |   1.824029   .7702408                      .3143851    3.333674
-----------------------------------------------------------------------------------
Note: 149 observations completely determined.  Standard errors questionable.

. ologit us_intervene_amer i.ccode t t2 t3 postcw log_cas us_gdp_growth provocation_new3 lag_us_cinc lag_adversary_cinc if sample_cow
> ==1, vce(cluster id)

Iteration 0:   log pseudolikelihood = -425.80231  
Iteration 1:   log pseudolikelihood = -368.47581  
Iteration 2:   log pseudolikelihood = -337.16383  
Iteration 3:   log pseudolikelihood = -334.72676  
Iteration 4:   log pseudolikelihood = -334.33131  
Iteration 5:   log pseudolikelihood = -334.26046  
Iteration 6:   log pseudolikelihood = -334.24454  
Iteration 7:   log pseudolikelihood = -334.24068  
Iteration 8:   log pseudolikelihood = -334.23987  
Iteration 9:   log pseudolikelihood =  -334.2397  
Iteration 10:  log pseudolikelihood = -334.23966  
Iteration 11:  log pseudolikelihood = -334.23965  

Ordered logistic regression                     Number of obs     =      1,248
                                                Wald chi2(31)     =          .
                                                Prob > chi2       =          .
Log pseudolikelihood = -334.23965               Pseudo R2         =     0.2150

                                          (Std. Err. adjusted for 33 clusters in id)
------------------------------------------------------------------------------------
                   |               Robust
 us_intervene_amer |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
             ccode |
              210  |   -.664087   .0224936   -29.52   0.000    -.7081735   -.6200004
              211  |  -1.455189   .0368458   -39.49   0.000    -1.527406   -1.382973
              212  |  -2.621078   .0469855   -55.78   0.000    -2.713168   -2.528988
              220  |  -.3030797   .0107344   -28.23   0.000    -.3241188   -.2820407
              230  |  -.6018167   .0767382    -7.84   0.000    -.7522208   -.4514127
              235  |  -1.138407   .0333445   -34.14   0.000    -1.203761   -1.073053
              255  |  -.2741196   .0179166   -15.30   0.000    -.3092355   -.2390038
              290  |  -1.378889   .2074986    -6.65   0.000    -1.785579    -.972199
              310  |  -1.378889   .2074986    -6.65   0.000    -1.785579    -.972199
              316  |  -1.378889   .2074986    -6.65   0.000    -1.785579    -.972199
              317  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              325  |   -1.12752   .0307022   -36.72   0.000    -1.187695   -1.067344
              339  |  -16.74275   1.142969   -14.65   0.000    -18.98293   -14.50257
              344  |  -16.74275   1.142969   -14.65   0.000    -18.98293   -14.50257
              349  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              350  |  -1.126109   .0308454   -36.51   0.000    -1.186565   -1.065653
              355  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              360  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              366  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              367  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              368  |    -16.648   1.108128   -15.02   0.000    -18.81989   -14.47611
              385  |  -1.125435    .030068   -37.43   0.000    -1.184367   -1.066502
              390  |  -1.126536   .0305837   -36.83   0.000    -1.186479   -1.066593
              395  |  -2.621078   .0469855   -55.78   0.000    -2.713168   -2.528988
              640  |  -.1528164   .0082988   -18.41   0.000    -.1690818    -.136551
              713  |   .8259211   .1930064     4.28   0.000     .4476355    1.204207
              732  |   1.717434    .124935    13.75   0.000     1.472566    1.962302
              740  |  -.0026056    .124897    -0.02   0.983    -.2473991     .242188
              770  |  -.2057422   .0385196    -5.34   0.000    -.2812392   -.1302451
              840  |  -15.55741   1.023654   -15.20   0.000    -17.56373   -13.55108
              900  |  -1.000033   .1275049    -7.84   0.000    -1.249938   -.7501275
              920  |  -15.62773   1.026748   -15.22   0.000    -17.64012   -13.61534
                   |
                 t |  -.3374374    .323511    -1.04   0.297    -.9715072    .2966325
                t2 |   .0078546   .0076322     1.03   0.303    -.0071043    .0228135
                t3 |  -.0000601   .0000586    -1.03   0.305    -.0001749    .0000547
            postcw |  -.4296052   .4155693    -1.03   0.301    -1.244106    .3848956
           log_cas |  -.2715134   .0882706    -3.08   0.002    -.4445205   -.0985063
     us_gdp_growth |  -.0885436   .0502416    -1.76   0.078    -.1870154    .0099282
  provocation_new3 |  -.3533622   .2731612    -1.29   0.196    -.8887483    .1820238
       lag_us_cinc |  -.1421868   .2180772    -0.65   0.514    -.5696103    .2852366
lag_adversary_cinc |  -.2293626   .0329709    -6.96   0.000    -.2939845   -.1647407
-------------------+----------------------------------------------------------------
             /cut1 |  -8.882788    7.56122                     -23.70251     5.93693
             /cut2 |  -6.973052   7.593424                     -21.85589    7.909786
------------------------------------------------------------------------------------
Note: 149 observations completely determined.  Standard errors questionable.

. nbreg withdrawal t t2 t3 postcw log_cas us_gdp_growth  if country=="France", vce(robust)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -55.588473  
Iteration 1:   log pseudolikelihood = -53.531349  
Iteration 2:   log pseudolikelihood = -53.500943  
Iteration 3:   log pseudolikelihood = -53.500873  
Iteration 4:   log pseudolikelihood = -53.500873  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -70.851636  
Iteration 1:   log pseudolikelihood = -70.726467  
Iteration 2:   log pseudolikelihood = -70.724067  
Iteration 3:   log pseudolikelihood = -70.724066  

Fitting full model:

Iteration 0:   log pseudolikelihood = -70.724066  
Iteration 1:   log pseudolikelihood = -55.287232  (not concave)
Iteration 2:   log pseudolikelihood = -54.804547  
Iteration 3:   log pseudolikelihood = -52.798731  
Iteration 4:   log pseudolikelihood = -52.740117  
Iteration 5:   log pseudolikelihood = -52.736182  
Iteration 6:   log pseudolikelihood =  -52.73617  
Iteration 7:   log pseudolikelihood =  -52.73617  

Negative binomial regression                    Number of obs     =         60
                                                Wald chi2(6)      =      26.95
Dispersion           = mean                     Prob > chi2       =     0.0001
Log pseudolikelihood =  -52.73617               Pseudo R2         =     0.2543

-------------------------------------------------------------------------------
              |               Robust
   withdrawal |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
            t |  -.4819448   .1502799    -3.21   0.001    -.7764879   -.1874017
           t2 |   .0353662   .0090539     3.91   0.000     .0176209    .0531115
           t3 |  -.0004854   .0001168    -4.16   0.000    -.0007143   -.0002564
       postcw |   -.173197   .5793415    -0.30   0.765    -1.308686    .9622915
      log_cas |   .6251966   .1577251     3.96   0.000     .3160611    .9343322
us_gdp_growth |   .0851669   .1152684     0.74   0.460    -.1407549    .3110887
        _cons |  -5.769074   1.791069    -3.22   0.001    -9.279504   -2.258643
--------------+----------------------------------------------------------------
     /lnalpha |  -1.680543   1.008256                     -3.656688    .2956023
--------------+----------------------------------------------------------------
        alpha |   .1862729   .1878107                      .0258179    1.343936
-------------------------------------------------------------------------------

. nbreg withdrawal t t2 t3 postcw log_cas us_gdp_growth provocation_new3 lag_us_cinc lag_adversary_cinc lag_MID_weighted_mean if coun
> try=="France", vce(robust)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -54.373468  
Iteration 1:   log pseudolikelihood = -52.473751  
Iteration 2:   log pseudolikelihood = -52.445156  
Iteration 3:   log pseudolikelihood = -52.445096  
Iteration 4:   log pseudolikelihood = -52.445096  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -70.851636  
Iteration 1:   log pseudolikelihood = -70.726467  
Iteration 2:   log pseudolikelihood = -70.724067  
Iteration 3:   log pseudolikelihood = -70.724066  

Fitting full model:

Iteration 0:   log pseudolikelihood = -70.724066  (not concave)
Iteration 1:   log pseudolikelihood = -68.953613  
Iteration 2:   log pseudolikelihood = -55.738681  (not concave)
Iteration 3:   log pseudolikelihood = -55.369574  
Iteration 4:   log pseudolikelihood =  -52.17772  
Iteration 5:   log pseudolikelihood = -51.836618  
Iteration 6:   log pseudolikelihood = -51.817664  
Iteration 7:   log pseudolikelihood = -51.817595  
Iteration 8:   log pseudolikelihood = -51.817595  

Negative binomial regression                    Number of obs     =         60
                                                Wald chi2(10)     =      38.63
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -51.817595               Pseudo R2         =     0.2673

---------------------------------------------------------------------------------------
                      |               Robust
           withdrawal |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
                    t |  -.3114349    .236023    -1.32   0.187    -.7740315    .1511617
                   t2 |   .0324817   .0087454     3.71   0.000     .0153409    .0496224
                   t3 |  -.0004704   .0001083    -4.34   0.000    -.0006827   -.0002581
               postcw |  -.6871528   .9772872    -0.70   0.482    -2.602601    1.228295
              log_cas |   .5782552   .1559579     3.71   0.000     .2725833     .883927
        us_gdp_growth |   .0950429   .1359194     0.70   0.484    -.1713542      .36144
     provocation_new3 |   -.464316   .3947271    -1.18   0.239    -1.237967    .3093349
          lag_us_cinc |   .1863499    .220696     0.84   0.398    -.2462063    .6189062
   lag_adversary_cinc |   .0139447   .1292065     0.11   0.914    -.2392954    .2671847
lag_MID_weighted_mean |   .1198739   .2145805     0.56   0.576    -.3006961     .540444
                _cons |  -11.65975   8.323967    -1.40   0.161    -27.97443    4.654924
----------------------+----------------------------------------------------------------
             /lnalpha |  -1.769463   1.158111                     -4.039319    .5003941
----------------------+----------------------------------------------------------------
                alpha |   .1704245   .1973706                      .0176095    1.649371
---------------------------------------------------------------------------------------

. reg goldstein_usa_soviet t log_cas us_gdp_growth if country=="France", vce(robust)

Linear regression                               Number of obs     =         25
                                                F(3, 21)          =       2.99
                                                Prob > F          =     0.0541
                                                R-squared         =     0.2896
                                                Root MSE          =     299.65

-------------------------------------------------------------------------------
              |               Robust
goldstein_u~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
            t |   26.53944   14.34767     1.85   0.078    -3.298165    56.37705
      log_cas |   84.63373   30.55565     2.77   0.011     21.08978    148.1777
us_gdp_growth |  -6.766458     22.995    -0.29   0.771    -54.58719    41.05427
        _cons |  -1166.893   491.3653    -2.37   0.027    -2188.743   -145.0427
-------------------------------------------------------------------------------

. reg goldstein_usa_soviet t log_cas us_gdp_growth provocation_new3 lag_us_cinc lag_adversary_cinc lag_MID_weighted_mean if country==
> "France", vce(robust)

Linear regression                               Number of obs     =         25
                                                F(7, 17)          =       2.38
                                                Prob > F          =     0.0684
                                                R-squared         =     0.5779
                                                Root MSE          =     256.71

---------------------------------------------------------------------------------------
                      |               Robust
 goldstein_usa_soviet |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
                    t |   40.79428   14.39419     2.83   0.011     10.42519    71.16337
              log_cas |   100.3145   54.06738     1.86   0.081    -13.75772    214.3867
        us_gdp_growth |  -15.59827   20.90777    -0.75   0.466    -59.70981    28.51326
     provocation_new3 |  -316.9785   87.23755    -3.63   0.002    -501.0337   -132.9234
          lag_us_cinc |    9.38237   78.16056     0.12   0.906     -155.522    174.2867
   lag_adversary_cinc |  -58.45009    197.032    -0.30   0.770    -474.1514    357.2512
lag_MID_weighted_mean |  -114.7118   70.90625    -1.62   0.124    -264.3109    34.88733
                _cons |  -308.1264   4172.742    -0.07   0.942    -9111.842    8495.589
---------------------------------------------------------------------------------------

. 
. 
. *Table A1
. sutex statements_americas lag_log_gdp lag_latency_pilot lag_nwcapability lag_democracy lag_log_trade log_distance MID_movingavg_not
> initiator MID_movingavg_aggressor log_cas us_gdp_growth warlength misery2 lag_adversary_cinc provocation_new3 lag_us_cinc log_dista
> nce log_distance_us lag_rivalry_thompson lag_rivalry_shared lag_log_gdppc democrat firstyear secondterm lag_troops if sample_cow==1
> , labels minmax nobs
%------- Begin LaTeX code -------%

\begin{table}[htbp]\centering \caption{Summary statistics \label{sumstat}}
\begin{tabular}{l c c c c c}\hline\hline
\multicolumn{1}{c}{\textbf{Variable}} & \textbf{Mean}
 & \textbf{Std. Dev.}& \textbf{Min.} &  \textbf{Max.} & \textbf{N}\\ \hline
Statements & 0.358 & 1.008 & 0 & 15 & 1258\\
GDP (log) & 25.816 & 1.621 & 20.78 & 29.039 & 1248\\
Nuclear latency & 0.144 & 0.351 & 0 & 1 & 1248\\
Possesses nuclear weapons & 0.105 & 0.307 & 0 & 1 & 1248\\
Democracy & 0.872 & 0.334 & 0 & 1 & 1248\\
Trade with US (log) & 22.327 & 1.683 & 18.11 & 26.24 & 1244\\
Distance to adversary (log) & 7.57 & 0.661 & 6.261 & 9.277 & 1258\\
MIDs (weighted), not initiator & 1.427 & 1.988 & 0 & 12 & 1248\\
MIDs (weighted), initiator & 1.125 & 2.295 & 0 & 20 & 1248\\
War casualties (3-yr moving avg) & 3.604 & 3.535 & 0 & 9.499 & 1258\\
US GDP growth & 3.083 & 2.521 & -3.588 & 7.754 & 1248\\
War duration & 2.188 & 2.778 & 0 & 9 & 1258\\
US economic misery & 9.481 & 3.409 & 3.725 & 20.675 & 1258\\
Adversary CINC & 13.373 & 5.491 & 3.935 & 20.819 & 1248\\
Adversary aggression & 0.354 & 0.478 & 0 & 1 & 1258\\
US CINC & 17.445 & 4.893 & 12.959 & 31.95 & 1248\\
Distance to adversary (log) & 7.57 & 0.661 & 6.261 & 9.277 & 1258\\
Distance from US (log) & 8.970 & 0.335 & 8.418 & 9.676 & 1258\\
Rivalries (not shared w/ US) & 0.307 & 0.649 & 0 & 2 & 1248\\
Rivalries (shared w/ US) & 0.116 & 0.321 & 0 & 1 & 1248\\
GDPpc (log) & 9.372 & 0.903 & 6.864 & 10.996 & 1248\\
Democrat & 0.398 & 0.49 & 0 & 1 & 1258\\
First year of presidency & 0.181 & 0.385 & 0 & 1 & 1258\\
Lame duck President & 0.313 & 0.464 & 0 & 1 & 1258\\
US troops (thousands) & 18.305 & 47.493 & 0 & 326.863 & 1248\\
\hline
\end{tabular}
\end{table}
%------- End LaTeX code -------%

. 
. *Table A2
. pwcorr statements_americas visits assurances_weis weis_cns lag_troops if sample_cow==1 & postcw==0

             | statem~s   visits assura~s weis_c~2 lag_tr~s
-------------+---------------------------------------------
statements~s |   1.0000 
      visits |   0.1079   1.0000 
assurances~s |   0.2047   0.1604   1.0000 
   weis_cns2 |   0.0878   0.3542   0.3080   1.0000 
  lag_troops |   0.0012   0.2486   0.2711   0.2893   1.0000 

. 
. *Table A3
. pwcorr statements_americas visits assurances_kinglowe visit_kinglowe lag_troops if sample_cow==1 & postcw==1

             | statem~s   visits assura~e visit_~e lag_tr~s
-------------+---------------------------------------------
statements~s |   1.0000 
      visits |   0.1732   1.0000 
assurances~e |   0.2319  -0.0124   1.0000 
visit_king~e |   0.3778   0.4947   0.3372   1.0000 
  lag_troops |   0.1697   0.2874   0.2055   0.3469   1.0000 

. 
. *Table A4
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_log_gdppc democrat firstyear secondterm lag_troops adv_signal_last3 if sa
> mple_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1083.9639  
Iteration 1:   log pseudolikelihood = -873.02985  
Iteration 2:   log pseudolikelihood = -802.95029  
Iteration 3:   log pseudolikelihood = -801.15892  
Iteration 4:   log pseudolikelihood = -801.15394  
Iteration 5:   log pseudolikelihood = -801.15394  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -851.16473  
Iteration 1:   log pseudolikelihood = -801.41438  
Iteration 2:   log pseudolikelihood =  -775.4316  
Iteration 3:   log pseudolikelihood = -769.97884  
Iteration 4:   log pseudolikelihood = -769.48836  
Iteration 5:   log pseudolikelihood = -769.48551  
Iteration 6:   log pseudolikelihood = -769.48551  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(28)     =    4544.19
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -769.48551               Pseudo R2         =     0.1723

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.5494766    .313647    -1.75   0.080    -1.164213    .0652602
                        5  |   3.019564    .430437     7.02   0.000     2.175923    3.863205
                           |
                    postcw |   -.198943   .5727722    -0.35   0.728    -1.321556    .9236699
                         t |  -.2832458   .0869713    -3.26   0.001    -.4537064   -.1127852
                        t2 |    .006739   .0025931     2.60   0.009     .0016566    .0118215
                        t3 |  -.0000533   .0000267    -2.00   0.046    -.0001055   -1.04e-06
                   log_cas |   .0717195   .0334595     2.14   0.032       .00614     .137299
             us_gdp_growth |  -.0584853   .0278162    -2.10   0.036     -.113004   -.0039667
               lag_log_gdp |   .6071908   .2065887     2.94   0.003     .2022843    1.012097
         lag_latency_pilot |   .8960153   .1677134     5.34   0.000     .5673031    1.224728
          lag_nwcapability |   .9791221   .3410622     2.87   0.004     .3106525    1.647592
              log_distance |  -.3591865   .2049882    -1.75   0.080     -.760956    .0425829
           log_distance_us |  -.0018556   .5986631    -0.00   0.998    -1.175214    1.171503
MID_movingavg_notinitiator |    .000673   .0411954     0.02   0.987    -.0800684    .0814144
   MID_movingavg_aggressor |   .0217471   .0251943     0.86   0.388    -.0276329    .0711271
        lag_adversary_cinc |  -.0301712   .0228766    -1.32   0.187    -.0750085    .0146661
               lag_us_cinc |  -.2919824   .0792297    -3.69   0.000    -.4472698    -.136695
          provocation_new3 |   .0752043    .178449     0.42   0.673    -.2745493    .4249579
             lag_democracy |    .141823   .3878749     0.37   0.715    -.6183978    .9020438
             lag_log_trade |  -.4883555   .1874438    -2.61   0.009    -.8557386   -.1209724
      lag_rivalry_thompson |   .5373327   .1194107     4.50   0.000     .3032921    .7713733
        lag_rivalry_shared |  -.1084989   .2723295    -0.40   0.690     -.642255    .4252571
             lag_log_gdppc |  -.0714761   .1337663    -0.53   0.593    -.3336531     .190701
                  democrat |    .110758   .1919424     0.58   0.564    -.2654423    .4869582
                 firstyear |   .0643348   .1640038     0.39   0.695    -.2571067    .3857763
                secondterm |  -.3002959   .1486812    -2.02   0.043    -.5917057    -.008886
                lag_troops |  -.0045207   .0029921    -1.51   0.131     -.010385    .0013437
          adv_signal_last3 |   .1780183    .059767     2.98   0.003     .0608772    .2951594
                     _cons |   4.568077   4.886342     0.93   0.350    -5.008978    14.14513
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1896782   .3072115                     -.7918016    .4124452
---------------------------+----------------------------------------------------------------
                     alpha |   .8272253   .2541331                      .4530279    1.510507
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_terrdisputes lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id
> )

Fitting Poisson model:

Iteration 0:   log pseudolikelihood =  -828.6401  
Iteration 1:   log pseudolikelihood = -683.67258  
Iteration 2:   log pseudolikelihood = -643.66495  
Iteration 3:   log pseudolikelihood = -642.78585  
Iteration 4:   log pseudolikelihood = -642.78281  
Iteration 5:   log pseudolikelihood = -642.78281  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -791.89547  
Iteration 1:   log pseudolikelihood = -779.90758  
Iteration 2:   log pseudolikelihood = -756.14789  
Iteration 3:   log pseudolikelihood = -756.10078  
Iteration 4:   log pseudolikelihood = -756.10078  

Fitting full model:

Iteration 0:   log pseudolikelihood = -688.90967  
Iteration 1:   log pseudolikelihood = -653.04919  
Iteration 2:   log pseudolikelihood = -632.80115  
Iteration 3:   log pseudolikelihood = -630.68098  (backed up)
Iteration 4:   log pseudolikelihood = -620.64752  
Iteration 5:   log pseudolikelihood = -619.04278  
Iteration 6:   log pseudolikelihood = -618.68094  
Iteration 7:   log pseudolikelihood = -618.68012  
Iteration 8:   log pseudolikelihood = -618.68012  

Negative binomial regression                    Number of obs     =      1,015
                                                Wald chi2(21)     =          .
Dispersion           = mean                     Prob > chi2       =          .
Log pseudolikelihood = -618.68012               Pseudo R2         =     0.1817

                                                  (Std. Err. adjusted for 24 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.7929788   .2454588    -3.23   0.001    -1.274069   -.3118884
                        5  |    2.95169   .4454538     6.63   0.000     2.078617    3.824764
                           |
                    postcw |   .4904064    .461444     1.06   0.288    -.4140073     1.39482
                         t |  -.3071652   .0965454    -3.18   0.001    -.4963906   -.1179398
                        t2 |   .0078558    .003204     2.45   0.014     .0015762    .0141355
                        t3 |  -.0000735   .0000367    -2.00   0.045    -.0001454   -1.59e-06
                   log_cas |   .0776497   .0358851     2.16   0.030     .0073161    .1479833
             us_gdp_growth |  -.0417499   .0276331    -1.51   0.131    -.0959097    .0124099
               lag_log_gdp |   .4452946   .2111492     2.11   0.035     .0314497    .8591395
         lag_latency_pilot |   .8783654    .184676     4.76   0.000     .5164071    1.240324
          lag_nwcapability |   1.306802   .3579385     3.65   0.000     .6052557    2.008349
              log_distance |  -.0649578   .1710947    -0.38   0.704    -.4002973    .2703817
           log_distance_us |   -.667278   .4665043    -1.43   0.153     -1.58161    .2470535
MID_movingavg_notinitiator |   .0115565   .0433413     0.27   0.790    -.0733908    .0965039
   MID_movingavg_aggressor |    .037082   .0207675     1.79   0.074    -.0036215    .0777855
        lag_adversary_cinc |   .0219943   .0374229     0.59   0.557    -.0513531    .0953418
               lag_us_cinc |  -.2915864   .0844363    -3.45   0.001    -.4570785   -.1260943
          provocation_new3 |   .0223189   .2176701     0.10   0.918    -.4043066    .4489445
             lag_democracy |   .0263936   .3625971     0.07   0.942    -.6842836    .7370707
             lag_log_trade |  -.2824063   .2382923    -1.19   0.236    -.7494507    .1846381
      lag_rivalry_thompson |   .7509013   .1533393     4.90   0.000     .4503617    1.051441
        lag_rivalry_shared |   .0674251   .1662693     0.41   0.685    -.2584568    .3933069
          lag_terrdisputes |  -.2906721   .0833001    -3.49   0.000    -.4539374   -.1274068
                lag_troops |  -.0034745   .0028445    -1.22   0.222    -.0090497    .0021007
          adv_signal_last3 |   .0763934   .1022974     0.75   0.455    -.1241058    .2768926
                     _cons |    6.64287   5.255586     1.26   0.206    -3.657889    16.94363
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.3393372   .2991896                      -.925738    .2470637
---------------------------+----------------------------------------------------------------
                     alpha |   .7122423   .2130955                      .3962389    1.280261
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_cinc lag_troops adv_signal_last3  if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1305.6614  
Iteration 1:   log pseudolikelihood = -1169.9075  
Iteration 2:   log pseudolikelihood = -829.10204  
Iteration 3:   log pseudolikelihood = -816.76571  
Iteration 4:   log pseudolikelihood = -816.29204  
Iteration 5:   log pseudolikelihood = -816.29126  
Iteration 6:   log pseudolikelihood = -816.29126  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood =  -851.0071  
Iteration 1:   log pseudolikelihood = -788.92796  
Iteration 2:   log pseudolikelihood = -776.97626  
Iteration 3:   log pseudolikelihood = -776.69104  
Iteration 4:   log pseudolikelihood = -776.69023  
Iteration 5:   log pseudolikelihood = -776.69023  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(23)     =    2668.35
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -776.69023               Pseudo R2         =     0.1646

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   .0792266   .4799199     0.17   0.869    -.8613992    1.019852
                        5  |    2.52056   .6108161     4.13   0.000     1.323383    3.717738
                           |
                    postcw |   .2237276   .4763272     0.47   0.639    -.7098566    1.157312
                         t |  -.3209309   .0863378    -3.72   0.000    -.4901499   -.1517118
                        t2 |   .0070478   .0024402     2.89   0.004     .0022651    .0118305
                        t3 |  -.0000549   .0000244    -2.25   0.024    -.0001027   -7.15e-06
                   log_cas |   .0781864   .0307248     2.54   0.011     .0179668    .1384059
             us_gdp_growth |  -.0648327   .0242565    -2.67   0.008    -.1123746   -.0172907
               lag_log_gdp |   .6647514   .2178073     3.05   0.002      .237857    1.091646
         lag_latency_pilot |   .7952571   .1735551     4.58   0.000     .4550953    1.135419
          lag_nwcapability |    1.03173   .3080047     3.35   0.001      .428052    1.635408
              log_distance |  -.3819989   .1871329    -2.04   0.041    -.7487726   -.0152252
           log_distance_us |    .543328   .7226746     0.75   0.452    -.8730883    1.959744
MID_movingavg_notinitiator |   .0296551   .0440092     0.67   0.500    -.0566013    .1159115
   MID_movingavg_aggressor |   .0243116   .0273942     0.89   0.375    -.0293801    .0780033
        lag_adversary_cinc |  -.0272686   .0195882    -1.39   0.164    -.0656607    .0111235
               lag_us_cinc |  -.3550877   .0753643    -4.71   0.000     -.502799   -.2073765
          provocation_new3 |   .1705578   .1821485     0.94   0.349    -.1864467    .5275622
             lag_democracy |   .1807472   .3250099     0.56   0.578    -.4562604    .8177549
             lag_log_trade |  -.5473695    .206163    -2.66   0.008    -.9514416   -.1432975
          lag_rivalry_cinc |   1.020348   1.449424     0.70   0.481     -1.82047    3.861167
                lag_troops |  -.0039824   .0030991    -1.29   0.199    -.0100566    .0020918
          adv_signal_last3 |   .1177825   .0597398     1.97   0.049     .0006946    .2348703
                     _cons |   .9176263   6.506618     0.14   0.888    -11.83511    13.67036
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.0625364   .2889958                     -.6289578    .5038849
---------------------------+----------------------------------------------------------------
                     alpha |   .9393788   .2714765                      .5331472    1.655139
--------------------------------------------------------------------------------------------

. nbreg statements_americas lag_statements_americas MID_movingavg_notinitiator MID_movingavg_aggressor log_cas us_gdp_growth lag_adve
> rsary_cinc provocation_new3 lag_us_cinc adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -3308.5074  
Iteration 1:   log pseudolikelihood = -2033.5268  (backed up)
Iteration 2:   log pseudolikelihood = -1321.2204  
Iteration 3:   log pseudolikelihood = -980.29134  
Iteration 4:   log pseudolikelihood = -948.42198  
Iteration 5:   log pseudolikelihood = -947.14317  
Iteration 6:   log pseudolikelihood = -947.13586  
Iteration 7:   log pseudolikelihood = -947.13586  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -971.69494  
Iteration 1:   log pseudolikelihood = -921.48712  
Iteration 2:   log pseudolikelihood = -921.26821  
Iteration 3:   log pseudolikelihood = -921.26814  

Fitting full model:

Iteration 0:   log pseudolikelihood = -867.53213  
Iteration 1:   log pseudolikelihood =   -852.386  
Iteration 2:   log pseudolikelihood = -841.15855  
Iteration 3:   log pseudolikelihood = -841.04173  
Iteration 4:   log pseudolikelihood = -841.04166  

Negative binomial regression                    Number of obs     =      1,228
                                                Wald chi2(9)      =     140.46
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -841.04166               Pseudo R2         =     0.0871

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
   lag_statements_americas |   .3819511   .0512141     7.46   0.000     .2815733     .482329
MID_movingavg_notinitiator |   .1179753   .0436844     2.70   0.007     .0323555     .203595
   MID_movingavg_aggressor |   .0224241   .0374863     0.60   0.550    -.0510476    .0958959
                   log_cas |   .0357162    .019801     1.80   0.071     -.003093    .0745254
             us_gdp_growth |  -.0740494   .0250249    -2.96   0.003    -.1230974   -.0250014
        lag_adversary_cinc |   .0896657   .0175824     5.10   0.000     .0552049    .1241265
          provocation_new3 |  -.1410752   .1526412    -0.92   0.355    -.4402464    .1580961
               lag_us_cinc |  -.1235012   .0246812    -5.00   0.000    -.1718754   -.0751269
          adv_signal_last3 |   .2624377    .117258     2.24   0.025     .0326163    .4922591
                     _cons |  -.7163507   .4109897    -1.74   0.081    -1.521876    .0891742
---------------------------+----------------------------------------------------------------
                  /lnalpha |   .6654171   .1657795                      .3404952    .9903389
---------------------------+----------------------------------------------------------------
                     alpha |   1.945302   .3224911                      1.405644    2.692147
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster year)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =     434.33
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                (Std. Err. adjusted for 60 clusters in year)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .4489701    -1.09   0.276    -1.369213    .3907171
                        5  |   3.045549   .5019375     6.07   0.000      2.06177    4.029329
                           |
                    postcw |   .1874806   .3425848     0.55   0.584    -.4839733    .8589345
                         t |  -.3099749   .0617408    -5.02   0.000    -.4309847   -.1889652
                        t2 |    .006562   .0017884     3.67   0.000     .0030568    .0100673
                        t3 |  -.0000486   .0000184    -2.65   0.008    -.0000846   -.0000126
                   log_cas |   .0788582    .024504     3.22   0.001     .0308313    .1268852
             us_gdp_growth |  -.0605993   .0243901    -2.48   0.013     -.108403   -.0127956
               lag_log_gdp |   .5778804   .1862839     3.10   0.002     .2127706    .9429902
         lag_latency_pilot |   .9239081    .207564     4.45   0.000     .5170901    1.330726
          lag_nwcapability |   1.044292   .2449437     4.26   0.000     .5642113    1.524373
              log_distance |  -.4179051   .1902101    -2.20   0.028    -.7907101   -.0451001
           log_distance_us |   .1361485   .6076681     0.22   0.823    -1.054859    1.327156
MID_movingavg_notinitiator |   .0043977   .0384991     0.11   0.909    -.0710591    .0798545
   MID_movingavg_aggressor |   .0255337   .0291157     0.88   0.380     -.031532    .0825994
        lag_adversary_cinc |   -.031439   .0232736    -1.35   0.177    -.0770545    .0141765
               lag_us_cinc |  -.3437343   .0621972    -5.53   0.000    -.4656387   -.2218299
          provocation_new3 |   .1543866   .1252531     1.23   0.218    -.0911049    .3998781
             lag_democracy |   .1253958    .216324     0.58   0.562    -.2985915    .5493831
             lag_log_trade |  -.4839543   .1824991    -2.65   0.008     -.841646   -.1262626
      lag_rivalry_thompson |   .5396608   .1921993     2.81   0.005     .1629571    .9163645
        lag_rivalry_shared |  -.1653962   .2955351    -0.56   0.576    -.7446343    .4138419
                lag_troops |  -.0043163   .0027504    -1.57   0.117     -.009707    .0010744
          adv_signal_last3 |   .1650835   .1162604     1.42   0.156    -.0627827    .3929497
                     _cons |   5.254101   5.422577     0.97   0.333    -5.373955    15.88216
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2322821                     -.5705819     .339947
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2069826                      .5651964    1.404873
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_log_trade l
> ag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3  if sample_cow==1 & democracy==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -957.64026  
Iteration 1:   log pseudolikelihood = -842.67651  
Iteration 2:   log pseudolikelihood = -681.32396  
Iteration 3:   log pseudolikelihood = -674.57868  
Iteration 4:   log pseudolikelihood =  -674.4622  
Iteration 5:   log pseudolikelihood =  -674.4621  
Iteration 6:   log pseudolikelihood =  -674.4621  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -845.91542  
Iteration 1:   log pseudolikelihood = -796.98303  
Iteration 2:   log pseudolikelihood =  -790.0649  
Iteration 3:   log pseudolikelihood = -790.05718  
Iteration 4:   log pseudolikelihood = -790.05718  

Fitting full model:

Iteration 0:   log pseudolikelihood =   -722.216  
Iteration 1:   log pseudolikelihood = -659.64752  
Iteration 2:   log pseudolikelihood = -643.51189  
Iteration 3:   log pseudolikelihood = -642.90973  
Iteration 4:   log pseudolikelihood = -642.90357  
Iteration 5:   log pseudolikelihood = -642.90357  

Negative binomial regression                    Number of obs     =      1,087
                                                Wald chi2(23)     =    5762.32
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -642.90357               Pseudo R2         =     0.1863

                                                  (Std. Err. adjusted for 32 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.7703966   .3147997    -2.45   0.014    -1.387393   -.1534005
                        5  |   3.320826   .4730797     7.02   0.000     2.393607    4.248046
                           |
                    postcw |   .1783847   .5432174     0.33   0.743    -.8863019    1.243071
                         t |  -.3523229   .1015081    -3.47   0.001     -.551275   -.1533707
                        t2 |   .0077911   .0027473     2.84   0.005     .0024065    .0131757
                        t3 |  -.0000604   .0000255    -2.37   0.018    -.0001103   -.0000105
                   log_cas |   .1016701   .0272513     3.73   0.000     .0482585    .1550817
             us_gdp_growth |  -.0663448   .0304251    -2.18   0.029     -.125977   -.0067127
               lag_log_gdp |   .6577171   .1771833     3.71   0.000     .3104442     1.00499
         lag_latency_pilot |   .9942076   .1923401     5.17   0.000     .6172279    1.371187
          lag_nwcapability |   1.104577   .3058915     3.61   0.000     .5050406    1.704113
              log_distance |    -.52832   .1666377    -3.17   0.002     -.854924    -.201716
           log_distance_us |   .1489484   .6201358     0.24   0.810    -1.066495    1.364392
MID_movingavg_notinitiator |  -.0005521   .0476891    -0.01   0.991    -.0940211    .0929169
   MID_movingavg_aggressor |   .0316419   .0449923     0.70   0.482    -.0565414    .1198252
        lag_adversary_cinc |  -.0339761   .0254688    -1.33   0.182     -.083894    .0159419
               lag_us_cinc |  -.3935503    .078989    -4.98   0.000     -.548366   -.2387346
          provocation_new3 |    .186358   .1964773     0.95   0.343    -.1987304    .5714464
             lag_log_trade |   -.557285   .1673828    -3.33   0.001    -.8853493   -.2292207
      lag_rivalry_thompson |   .5783013   .1319227     4.38   0.000     .3197375    .8368652
        lag_rivalry_shared |  -.4070705   .2038577    -2.00   0.046    -.8066242   -.0075169
                lag_troops |  -.0073232   .0016553    -4.42   0.000    -.0105676   -.0040789
          adv_signal_last3 |   .1688421   .0684544     2.47   0.014     .0346739    .3030103
                     _cons |   6.884222   5.680419     1.21   0.226    -4.249195    18.01764
---------------------------+----------------------------------------------------------------
                  /lnalpha |   -.151199     .30653                     -.7519867    .4495886
---------------------------+----------------------------------------------------------------
                     alpha |   .8596766   .2635166                       .471429    1.567667
--------------------------------------------------------------------------------------------

. nbreg statements_net i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance log_
> distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy lag_lo
> g_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.4428  
Iteration 1:   log pseudolikelihood = -859.10456  
Iteration 2:   log pseudolikelihood = -801.62155  
Iteration 3:   log pseudolikelihood = -800.36001  
Iteration 4:   log pseudolikelihood = -800.35479  
Iteration 5:   log pseudolikelihood = -800.35479  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -970.99415  
Iteration 1:   log pseudolikelihood = -919.34041  
Iteration 2:   log pseudolikelihood =   -919.338  
Iteration 3:   log pseudolikelihood =   -919.338  

Fitting full model:

Iteration 0:   log pseudolikelihood = -841.30489  
Iteration 1:   log pseudolikelihood = -779.78783  
Iteration 2:   log pseudolikelihood = -764.71117  
Iteration 3:   log pseudolikelihood = -763.98198  
Iteration 4:   log pseudolikelihood = -763.97987  
Iteration 5:   log pseudolikelihood = -763.97987  

Negative binomial regression                    Number of obs     =      1,243
                                                Wald chi2(24)     =    2506.10
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -763.97987               Pseudo R2         =     0.1690

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
            statements_net |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4957856   .2574182    -1.93   0.054    -1.000316    .0087448
                        5  |    3.01943   .4602084     6.56   0.000     2.117438    3.921422
                           |
                    postcw |   .1838398   .4641449     0.40   0.692    -.7258675    1.093547
                         t |  -.2924948    .092401    -3.17   0.002    -.4735974   -.1113922
                        t2 |   .0058671   .0025812     2.27   0.023      .000808    .0109261
                        t3 |  -.0000411   .0000253    -1.62   0.104    -.0000906    8.47e-06
                   log_cas |   .0705639   .0322628     2.19   0.029     .0073299    .1337979
             us_gdp_growth |  -.0641367    .023827    -2.69   0.007    -.1108368   -.0174366
               lag_log_gdp |   .5910173   .1929531     3.06   0.002     .2128362    .9691985
         lag_latency_pilot |   .9412001   .1642711     5.73   0.000     .6192347    1.263166
          lag_nwcapability |   1.011677   .3117118     3.25   0.001     .4007328     1.62262
              log_distance |  -.4479166   .1699986    -2.63   0.008    -.7811077   -.1147256
           log_distance_us |   .1827046    .556657     0.33   0.743     -.908323    1.273732
MID_movingavg_notinitiator |    .010065   .0370161     0.27   0.786    -.0624853    .0826153
   MID_movingavg_aggressor |   .0283068   .0286759     0.99   0.324    -.0278969    .0845106
        lag_adversary_cinc |  -.0296466   .0224642    -1.32   0.187    -.0736756    .0143824
               lag_us_cinc |  -.3388503     .07523    -4.50   0.000    -.4862983   -.1914022
          provocation_new3 |   .1207106   .1843088     0.65   0.513     -.240528    .4819492
             lag_democracy |   .1802881   .3495158     0.52   0.606    -.5047502    .8653265
             lag_log_trade |  -.4759558   .1804079    -2.64   0.008    -.8295488   -.1223628
      lag_rivalry_thompson |   .5373879   .1188125     4.52   0.000     .3045197    .7702561
        lag_rivalry_shared |   -.245752   .2201876    -1.12   0.264    -.6773119    .1858078
                lag_troops |  -.0057706   .0021215    -2.72   0.007    -.0099286   -.0016126
          adv_signal_last3 |   .1596452   .0604482     2.64   0.008     .0411689    .2781216
                     _cons |   4.349091   5.442864     0.80   0.424    -6.318726    15.01691
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1100831   .2930773                     -.6845041    .4643379
---------------------------+----------------------------------------------------------------
                     alpha |   .8957597   .2625268                      .5043403     1.59096
--------------------------------------------------------------------------------------------

. 
. 
. *Table A5
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_cinc lag_latency_pilot lag_nwcapability log_distance lo
> g_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy lag_
> log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1250.1606  
Iteration 1:   log pseudolikelihood = -927.56761  
Iteration 2:   log pseudolikelihood = -824.11416  
Iteration 3:   log pseudolikelihood = -810.08267  
Iteration 4:   log pseudolikelihood = -810.04721  
Iteration 5:   log pseudolikelihood = -810.04721  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -848.98271  
Iteration 1:   log pseudolikelihood = -788.86835  
Iteration 2:   log pseudolikelihood = -775.05873  
Iteration 3:   log pseudolikelihood = -774.63259  
Iteration 4:   log pseudolikelihood = -774.63004  
Iteration 5:   log pseudolikelihood = -774.63004  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    4809.03
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -774.63004               Pseudo R2         =     0.1668

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.7618542    .266222    -2.86   0.004     -1.28364   -.2400688
                        5  |   1.576048   .4617058     3.41   0.001     .6711216    2.480975
                           |
                    postcw |    .193911   .4819199     0.40   0.687    -.7506347    1.138457
                         t |  -.2422851    .082387    -2.94   0.003    -.4037605   -.0808096
                        t2 |    .004781   .0023393     2.04   0.041      .000196     .009366
                        t3 |  -.0000321    .000023    -1.40   0.163    -.0000773     .000013
                   log_cas |   .0686315   .0308755     2.22   0.026     .0081167    .1291463
             us_gdp_growth |  -.0536707    .023896    -2.25   0.025     -.100506   -.0068353
                  lag_cinc |   .2591332   .0927582     2.79   0.005     .0773305     .440936
         lag_latency_pilot |   .6921669   .2220674     3.12   0.002     .2569228    1.127411
          lag_nwcapability |   .8696037   .3784104     2.30   0.022     .1279329    1.611275
              log_distance |  -.3949074   .1708596    -2.31   0.021    -.7297861   -.0600287
           log_distance_us |   1.542367   .6508484     2.37   0.018     .2667272    2.818006
MID_movingavg_notinitiator |   .0120514   .0363919     0.33   0.741    -.0592754    .0833782
   MID_movingavg_aggressor |    .033479   .0314208     1.07   0.287    -.0281046    .0950626
        lag_adversary_cinc |  -.0169006   .0265826    -0.64   0.525    -.0690015    .0352003
               lag_us_cinc |  -.3116857   .0712318    -4.38   0.000    -.4512976   -.1720739
          provocation_new3 |   .1484476   .1791834     0.83   0.407    -.2027453    .4996406
             lag_democracy |   .1547443   .3083383     0.50   0.616    -.4495877    .7590763
             lag_log_trade |  -.1190825   .0866015    -1.38   0.169    -.2888182    .0506532
      lag_rivalry_thompson |   .5145271    .138814     3.71   0.000     .2424567    .7865975
        lag_rivalry_shared |  -.1310834   .2193674    -0.60   0.550    -.5610356    .2988689
                lag_troops |  -.0057129   .0041118    -1.39   0.165    -.0137719    .0023461
          adv_signal_last3 |   .2430588     .07906     3.07   0.002     .0881039    .3980136
                     _cons |  -2.186655   5.735685    -0.38   0.703    -13.42839    9.055082
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1526736   .3303971                       -.80024    .4948928
---------------------------+----------------------------------------------------------------
                     alpha |   .8584098   .2836161                      .4492211    1.640322
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 warlength us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distan
> ce log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy
>  lag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1052.2861  
Iteration 1:   log pseudolikelihood = -863.08399  
Iteration 2:   log pseudolikelihood = -809.52962  
Iteration 3:   log pseudolikelihood = -808.29814  
Iteration 4:   log pseudolikelihood = -808.29388  
Iteration 5:   log pseudolikelihood = -808.29388  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.59421  
Iteration 1:   log pseudolikelihood = -786.81971  
Iteration 2:   log pseudolikelihood = -772.88375  
Iteration 3:   log pseudolikelihood = -772.40363  
Iteration 4:   log pseudolikelihood = -772.40196  
Iteration 5:   log pseudolikelihood = -772.40196  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    2845.99
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.40196               Pseudo R2         =     0.1692

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4799383   .2549808    -1.88   0.060    -.9796914    .0198148
                        5  |   2.973866   .4520279     6.58   0.000     2.087908    3.859824
                           |
                    postcw |   .0593715   .4209354     0.14   0.888    -.7656467    .8843897
                         t |  -.2286959   .0799892    -2.86   0.004    -.3854718   -.0719199
                        t2 |   .0054472   .0023676     2.30   0.021     .0008069    .0100875
                        t3 |  -.0000454   .0000239    -1.89   0.058    -.0000923    1.56e-06
                 warlength |   .0837191   .0309987     2.70   0.007     .0229627    .1444756
             us_gdp_growth |  -.0452954   .0247769    -1.83   0.068    -.0938572    .0032664
               lag_log_gdp |   .5613839   .2071335     2.71   0.007     .1554097    .9673582
         lag_latency_pilot |   .9178745   .1683721     5.45   0.000     .5878712    1.247878
          lag_nwcapability |   1.024779    .333658     3.07   0.002     .3708214    1.678737
              log_distance |  -.4135742   .1751403    -2.36   0.018    -.7568428   -.0703056
           log_distance_us |   .1888221   .5484996     0.34   0.731    -.8862175    1.263862
MID_movingavg_notinitiator |   .0159146    .036646     0.43   0.664    -.0559103    .0877394
   MID_movingavg_aggressor |   .0270033   .0285266     0.95   0.344    -.0289077    .0829144
        lag_adversary_cinc |  -.0306401   .0212449    -1.44   0.149    -.0722793    .0109991
               lag_us_cinc |  -.2283099    .061864    -3.69   0.000    -.3495611   -.1070587
          provocation_new3 |   .1301702   .1762944     0.74   0.460    -.2153604    .4757008
             lag_democracy |   .1261643   .3484073     0.36   0.717    -.5567015    .8090302
             lag_log_trade |   -.469961   .1998438    -2.35   0.019    -.8616477   -.0782744
      lag_rivalry_thompson |    .512699   .1245237     4.12   0.000      .268637    .7567611
        lag_rivalry_shared |  -.1720531   .2126884    -0.81   0.419    -.5889147    .2448085
                lag_troops |   -.004475   .0029883    -1.50   0.134    -.0103319    .0013819
          adv_signal_last3 |   .1597669   .0634479     2.52   0.012     .0354113    .2841225
                     _cons |   1.645903   4.919287     0.33   0.738    -7.995723    11.28753
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1297282   .3175226                     -.7520611    .4926047
---------------------------+----------------------------------------------------------------
                     alpha |   .8783341    .278891                      .4713939    1.636573
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas unemployment lag_log_gdp lag_latency_pilot lag_nwcapability log_distance 
> log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy la
> g_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1051.5284  
Iteration 1:   log pseudolikelihood = -862.89652  
Iteration 2:   log pseudolikelihood =  -809.6518  
Iteration 3:   log pseudolikelihood = -808.34672  
Iteration 4:   log pseudolikelihood = -808.34157  
Iteration 5:   log pseudolikelihood = -808.34157  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.48558  
Iteration 1:   log pseudolikelihood = -786.57529  
Iteration 2:   log pseudolikelihood = -772.44726  
Iteration 3:   log pseudolikelihood = -771.93304  
Iteration 4:   log pseudolikelihood = -771.93136  
Iteration 5:   log pseudolikelihood = -771.93136  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3792.70
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -771.93136               Pseudo R2         =     0.1697

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4445001    .261971    -1.70   0.090    -.9579538    .0689535
                        5  |   2.905867   .4736196     6.14   0.000     1.977589    3.834144
                           |
                    postcw |   .1180624   .4478914     0.26   0.792    -.7597886    .9959134
                         t |  -.2259129   .0794237    -2.84   0.004    -.3815805   -.0702454
                        t2 |   .0055109   .0024083     2.29   0.022     .0007907    .0102311
                        t3 |  -.0000469   .0000256    -1.83   0.067     -.000097    3.21e-06
                   log_cas |   .0841753   .0345745     2.43   0.015     .0164106    .1519401
              unemployment |   .1289435   .0652951     1.97   0.048     .0009675    .2569196
               lag_log_gdp |   .5433805   .2065457     2.63   0.009     .1385584    .9482025
         lag_latency_pilot |   .9141806   .1685897     5.42   0.000     .5837507     1.24461
          lag_nwcapability |   1.011529   .3343248     3.03   0.002      .356264    1.666793
              log_distance |  -.4034176   .1777077    -2.27   0.023    -.7517182    -.055117
           log_distance_us |   .2445947   .5830086     0.42   0.675    -.8980812    1.387271
MID_movingavg_notinitiator |   .0080776   .0386948     0.21   0.835    -.0677628    .0839179
   MID_movingavg_aggressor |   .0230761   .0258595     0.89   0.372    -.0276075    .0737597
        lag_adversary_cinc |  -.0335437   .0216212    -1.55   0.121    -.0759206    .0088331
               lag_us_cinc |  -.2302315   .0792493    -2.91   0.004    -.3855571   -.0749058
          provocation_new3 |   .1131361    .204791     0.55   0.581    -.2882469    .5145191
             lag_democracy |   .1288841   .3577108     0.36   0.719    -.5722163    .8299844
             lag_log_trade |  -.4383776   .1956612    -2.24   0.025    -.8218665   -.0548887
      lag_rivalry_thompson |   .5215781     .13011     4.01   0.000     .2665672     .776589
        lag_rivalry_shared |   -.111778   .2193757    -0.51   0.610    -.5417466    .3181906
                lag_troops |  -.0045183     .00301    -1.50   0.133    -.0104177    .0013811
          adv_signal_last3 |   .1539437   .0660802     2.33   0.020     .0244289    .2834586
                     _cons |  -.1813984   6.149482    -0.03   0.976    -12.23416    11.87136
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1297377   .2991075                     -.7159777    .4565022
---------------------------+----------------------------------------------------------------
                     alpha |   .8783258   .2627138                      .4887141    1.578543
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas inflation lag_log_gdp lag_latency_pilot lag_nwcapability log_distance log
> _distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy lag_l
> og_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1058.5437  
Iteration 1:   log pseudolikelihood = -867.37861  
Iteration 2:   log pseudolikelihood = -812.77403  
Iteration 3:   log pseudolikelihood =  -811.5335  
Iteration 4:   log pseudolikelihood = -811.52907  
Iteration 5:   log pseudolikelihood = -811.52907  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -850.66451  
Iteration 1:   log pseudolikelihood = -787.88726  
Iteration 2:   log pseudolikelihood = -774.60766  
Iteration 3:   log pseudolikelihood = -774.15985  
Iteration 4:   log pseudolikelihood = -774.15841  
Iteration 5:   log pseudolikelihood = -774.15841  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    4125.43
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -774.15841               Pseudo R2         =     0.1673

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4930588   .2567616    -1.92   0.055    -.9963022    .0101847
                        5  |   2.987611   .4673648     6.39   0.000     2.071592    3.903629
                           |
                    postcw |   .2314264   .4781244     0.48   0.628    -.7056803    1.168533
                         t |  -.2278123   .0769026    -2.96   0.003    -.3785386    -.077086
                        t2 |   .0043704   .0021679     2.02   0.044     .0001215    .0086193
                        t3 |  -.0000283   .0000224    -1.26   0.207    -.0000723    .0000157
                   log_cas |   .0598333   .0339523     1.76   0.078    -.0067121    .1263787
                 inflation |   .0284209   .0284788     1.00   0.318    -.0273966    .0842384
               lag_log_gdp |   .5576313   .1951525     2.86   0.004     .1751394    .9401231
         lag_latency_pilot |   .9240203   .1649386     5.60   0.000     .6007466    1.247294
          lag_nwcapability |    1.04267   .3319858     3.14   0.002     .3919896     1.69335
              log_distance |  -.4200299   .1716054    -2.45   0.014    -.7563703   -.0836894
           log_distance_us |   .1758165   .5624915     0.31   0.755    -.9266465     1.27828
MID_movingavg_notinitiator |   .0009074   .0390653     0.02   0.981    -.0756591    .0774739
   MID_movingavg_aggressor |   .0243171   .0285947     0.85   0.395    -.0317274    .0803617
        lag_adversary_cinc |  -.0289697    .022872    -1.27   0.205     -.073798    .0158586
               lag_us_cinc |  -.2810523    .075029    -3.75   0.000    -.4281064   -.1339982
          provocation_new3 |   .2102419   .1607165     1.31   0.191    -.1047566    .5252403
             lag_democracy |   .1142881   .3457397     0.33   0.741    -.5633492    .7919254
             lag_log_trade |  -.4597544   .1891269    -2.43   0.015    -.8304362   -.0890725
      lag_rivalry_thompson |   .5547897   .1220223     4.55   0.000     .3156304    .7939489
        lag_rivalry_shared |  -.1736194   .2288705    -0.76   0.448    -.6221973    .2749585
                lag_troops |  -.0042803   .0031193    -1.37   0.170     -.010394    .0018334
          adv_signal_last3 |    .162038   .0644703     2.51   0.012     .0356785    .2883975
                     _cons |   2.570195    5.40797     0.48   0.635    -8.029231    13.16962
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1121216   .2931238                     -.6866336    .4623905
---------------------------+----------------------------------------------------------------
                     alpha |   .8939356   .2620338                      .5032674    1.587865
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas unemployment inflation lag_log_gdp lag_latency_pilot lag_nwcapability log
> _distance log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_de
> mocracy lag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1050.1284  
Iteration 1:   log pseudolikelihood = -862.07205  
Iteration 2:   log pseudolikelihood = -808.84795  
Iteration 3:   log pseudolikelihood = -807.51565  
Iteration 4:   log pseudolikelihood = -807.51038  
Iteration 5:   log pseudolikelihood = -807.51038  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -848.81242  
Iteration 1:   log pseudolikelihood = -785.15963  
Iteration 2:   log pseudolikelihood = -770.91826  
Iteration 3:   log pseudolikelihood =  -770.3787  
Iteration 4:   log pseudolikelihood = -770.37698  
Iteration 5:   log pseudolikelihood = -770.37698  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(25)     =    4675.43
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -770.37698               Pseudo R2         =     0.1713

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4457272   .2638969    -1.69   0.091    -.9629557    .0715014
                        5  |    2.96725   .4848412     6.12   0.000     2.016979    3.917522
                           |
                    postcw |   .0183621   .4537933     0.04   0.968    -.8710564    .9077806
                         t |  -.1790461   .0757906    -2.36   0.018    -.3275929   -.0304993
                        t2 |   .0047875    .002343     2.04   0.041     .0001953    .0093797
                        t3 |   -.000042   .0000252    -1.67   0.095    -.0000914    7.35e-06
                   log_cas |   .0718193   .0362372     1.98   0.047     .0007957    .1428428
              unemployment |   .1568808   .0606848     2.59   0.010     .0379407     .275821
                 inflation |   .0516077   .0282862     1.82   0.068    -.0038322    .1070477
               lag_log_gdp |   .5716701   .2054008     2.78   0.005     .1690918    .9742483
         lag_latency_pilot |   .9166393   .1747854     5.24   0.000     .5740662    1.259212
          lag_nwcapability |   1.017505   .3373888     3.02   0.003     .3562348    1.678775
              log_distance |  -.4058972   .1716569    -2.36   0.018    -.7423386   -.0694558
           log_distance_us |   .1875304   .5852615     0.32   0.749    -.9595611    1.334622
MID_movingavg_notinitiator |   .0158579   .0384651     0.41   0.680    -.0595324    .0912482
   MID_movingavg_aggressor |   .0265234   .0285591     0.93   0.353    -.0294514    .0824982
        lag_adversary_cinc |  -.0319808   .0215403    -1.48   0.138     -.074199    .0102373
               lag_us_cinc |  -.1546126   .0712514    -2.17   0.030    -.2942627   -.0149625
          provocation_new3 |   .0072779   .1794417     0.04   0.968    -.3444213    .3589771
             lag_democracy |   .1399856   .3621049     0.39   0.699    -.5697269    .8496981
             lag_log_trade |  -.4712478   .2001432    -2.35   0.019    -.8635213   -.0789744
      lag_rivalry_thompson |   .5068506   .1274157     3.98   0.000     .2571204    .7565807
        lag_rivalry_shared |  -.1165884   .2184642    -0.53   0.594    -.5447705    .3115936
                lag_troops |   -.004464   .0028771    -1.55   0.121     -.010103     .001175
          adv_signal_last3 |   .1544898   .0671757     2.30   0.021     .0228279    .2861517
                     _cons |  -2.106539   5.881178    -0.36   0.720    -13.63344    9.420358
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1318605   .2818138                     -.6842054    .4204844
---------------------------+----------------------------------------------------------------
                     alpha |   .8764632   .2469995                      .5044909    1.522699
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas misery2 lag_log_gdp lag_latency_pilot lag_nwcapability log_distance log_d
> istance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy lag_log
> _trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1054.9298  
Iteration 1:   log pseudolikelihood = -865.58299  
Iteration 2:   log pseudolikelihood = -811.39566  
Iteration 3:   log pseudolikelihood = -810.09523  
Iteration 4:   log pseudolikelihood = -810.09043  
Iteration 5:   log pseudolikelihood = -810.09043  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.56345  
Iteration 1:   log pseudolikelihood = -786.03832  
Iteration 2:   log pseudolikelihood = -772.59782  
Iteration 3:   log pseudolikelihood = -772.14454  
Iteration 4:   log pseudolikelihood = -772.14307  
Iteration 5:   log pseudolikelihood = -772.14306  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3551.86
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.14306               Pseudo R2         =     0.1694

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4791932   .2587206    -1.85   0.064    -.9862762    .0278898
                        5  |   3.016146   .4726787     6.38   0.000     2.089713    3.942579
                           |
                    postcw |   .1021952    .473989     0.22   0.829    -.8268061    1.031196
                         t |  -.1842947   .0722242    -2.55   0.011    -.3258514   -.0427379
                        t2 |   .0040672   .0020915     1.94   0.052    -.0000321    .0081665
                        t3 |  -.0000298   .0000219    -1.36   0.174    -.0000727    .0000132
                   log_cas |   .0563736   .0328358     1.72   0.086    -.0079834    .1207306
                   misery2 |   .0644801   .0247998     2.60   0.009     .0158733    .1130869
               lag_log_gdp |   .5779503   .1989563     2.90   0.004      .188003    .9678975
         lag_latency_pilot |   .9230483   .1706883     5.41   0.000     .5885053    1.257591
          lag_nwcapability |   1.038273    .333673     3.11   0.002     .3842857     1.69226
              log_distance |  -.4166623   .1705773    -2.44   0.015    -.7509876    -.082337
           log_distance_us |   .1467734   .5607955     0.26   0.794    -.9523656    1.245912
MID_movingavg_notinitiator |   .0099634   .0391759     0.25   0.799      -.06682    .0867469
   MID_movingavg_aggressor |   .0269395    .029144     0.92   0.355    -.0301817    .0840608
        lag_adversary_cinc |  -.0291017    .022314    -1.30   0.192    -.0728363     .014633
               lag_us_cinc |   -.196307   .0743718    -2.64   0.008     -.342073   -.0505409
          provocation_new3 |   .0855288   .1648789     0.52   0.604     -.237628    .4086856
             lag_democracy |   .1280527   .3527372     0.36   0.717    -.5632995    .8194049
             lag_log_trade |  -.4815468   .1935652    -2.49   0.013    -.8609277    -.102166
      lag_rivalry_thompson |   .5319065    .122272     4.35   0.000     .2922578    .7715552
        lag_rivalry_shared |  -.1589999   .2241454    -0.71   0.478    -.5983168    .2803171
                lag_troops |  -.0043015   .0029468    -1.46   0.144    -.0100771    .0014742
          adv_signal_last3 |   .1594216   .0666768     2.39   0.017     .0287374    .2901057
                     _cons |  -.0486895   5.583269    -0.01   0.993     -10.9917    10.89432
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1186593   .2799869                     -.6674236     .430105
---------------------------+----------------------------------------------------------------
                     alpha |   .8881104   .2486593                      .5130287    1.537419
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas_5yrs us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_dis
> tance log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democr
> acy lag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1053.6408  
Iteration 1:   log pseudolikelihood =  -863.7698  
Iteration 2:   log pseudolikelihood = -810.42493  
Iteration 3:   log pseudolikelihood = -809.21495  
Iteration 4:   log pseudolikelihood = -809.21095  
Iteration 5:   log pseudolikelihood = -809.21095  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.96968  
Iteration 1:   log pseudolikelihood = -787.08552  
Iteration 2:   log pseudolikelihood =  -772.9337  
Iteration 3:   log pseudolikelihood = -772.39277  
Iteration 4:   log pseudolikelihood = -772.39105  
Iteration 5:   log pseudolikelihood = -772.39105  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    2128.99
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.39105               Pseudo R2         =     0.1692

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.4805107   .2581738    -1.86   0.063    -.9865221    .0255007
                        5  |   3.039972   .4593854     6.62   0.000     2.139593    3.940351
                           |
                    postcw |   .1566416   .4399219     0.36   0.722    -.7055894    1.018873
                         t |  -.2836946   .0733054    -3.87   0.000    -.4273705   -.1400187
                        t2 |   .0061588   .0021888     2.81   0.005     .0018689    .0104487
                        t3 |  -.0000465    .000022    -2.12   0.034    -.0000896   -3.46e-06
              log_cas_5yrs |   .0765647   .0266676     2.87   0.004     .0242971    .1288323
             us_gdp_growth |  -.0551153   .0238019    -2.32   0.021    -.1017662   -.0084644
               lag_log_gdp |   .5736021   .2012231     2.85   0.004     .1792121     .967992
         lag_latency_pilot |   .9291995   .1729965     5.37   0.000     .5901326    1.268266
          lag_nwcapability |   1.043382   .3330326     3.13   0.002     .3906505    1.696114
              log_distance |  -.4202913   .1743995    -2.41   0.016    -.7621081   -.0784746
           log_distance_us |   .1419058   .5480732     0.26   0.796     -.932298     1.21611
MID_movingavg_notinitiator |   .0103243   .0377329     0.27   0.784    -.0636308    .0842793
   MID_movingavg_aggressor |   .0251523   .0289017     0.87   0.384     -.031494    .0817986
        lag_adversary_cinc |  -.0305702   .0220927    -1.38   0.166     -.073871    .0127307
               lag_us_cinc |  -.3185908   .0603042    -5.28   0.000    -.4367849   -.2003967
          provocation_new3 |   .1464087   .1789782     0.82   0.413    -.2043822    .4971995
             lag_democracy |   .1372878   .3553518     0.39   0.699     -.559189    .8337645
             lag_log_trade |  -.4860604    .192974    -2.52   0.012    -.8642825   -.1078383
      lag_rivalry_thompson |   .5297163   .1228055     4.31   0.000     .2890218    .7704107
        lag_rivalry_shared |  -.1778167    .224663    -0.79   0.429    -.6181481    .2625147
                lag_troops |   -.004379    .003073    -1.43   0.154     -.010402    .0016439
          adv_signal_last3 |   .1694119   .0634418     2.67   0.008     .0450684    .2937555
                     _cons |   4.457599   5.112478     0.87   0.383    -5.562674    14.47787
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1256899   .3022482                     -.7180855    .4667057
---------------------------+----------------------------------------------------------------
                     alpha |   .8818882   .2665491                       .487685    1.594732
--------------------------------------------------------------------------------------------

. 
. 
. *Table A6
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_atop==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1025.0388  
Iteration 1:   log pseudolikelihood = -878.31856  
Iteration 2:   log pseudolikelihood = -874.46271  
Iteration 3:   log pseudolikelihood = -874.44619  
Iteration 4:   log pseudolikelihood = -874.44619  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -1061.6021  
Iteration 1:   log pseudolikelihood =  -1052.081  
Iteration 2:   log pseudolikelihood = -1007.1802  
Iteration 3:   log pseudolikelihood = -1007.1752  
Iteration 4:   log pseudolikelihood = -1007.1752  

Fitting full model:

Iteration 0:   log pseudolikelihood = -920.80337  
Iteration 1:   log pseudolikelihood = -854.25119  
Iteration 2:   log pseudolikelihood = -837.12521  
Iteration 3:   log pseudolikelihood = -836.24858  
Iteration 4:   log pseudolikelihood = -836.24542  
Iteration 5:   log pseudolikelihood = -836.24542  

Negative binomial regression                    Number of obs     =      1,310
                                                Wald chi2(24)     =    3999.41
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -836.24542               Pseudo R2         =     0.1697

                                                  (Std. Err. adjusted for 36 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.3632018   .2959519    -1.23   0.220    -.9432568    .2168532
                        5  |   2.646087   .5193343     5.10   0.000      1.62821    3.663964
                           |
                    postcw |   .2123926   .4378448     0.49   0.628    -.6457674    1.070553
                         t |  -.2460574    .097016    -2.54   0.011    -.4362054   -.0559095
                        t2 |   .0047202   .0026407     1.79   0.074    -.0004554    .0098958
                        t3 |   -.000032    .000025    -1.28   0.201     -.000081    .0000171
                   log_cas |   .0690132   .0313347     2.20   0.028     .0075984     .130428
             us_gdp_growth |  -.0507682   .0217008    -2.34   0.019     -.093301   -.0082353
               lag_log_gdp |   .3650867   .1583215     2.31   0.021     .0547823    .6753911
         lag_latency_pilot |   .8780373   .1720303     5.10   0.000     .5408642     1.21521
          lag_nwcapability |   .9727722   .3469213     2.80   0.005     .2928189    1.652726
              log_distance |  -.4136839     .18509    -2.24   0.025    -.7764537   -.0509142
           log_distance_us |   .4641907   .6373913     0.73   0.466    -.7850734    1.713455
MID_movingavg_notinitiator |   .0240106   .0383162     0.63   0.531    -.0510878    .0991091
   MID_movingavg_aggressor |   .0249145    .028278     0.88   0.378    -.0305095    .0803384
        lag_adversary_cinc |  -.0267984   .0229633    -1.17   0.243    -.0718055    .0182088
               lag_us_cinc |   -.307477   .0756636    -4.06   0.000    -.4557749   -.1591791
          provocation_new3 |   .2010139   .1735216     1.16   0.247    -.1390822      .54111
             lag_democracy |   .1862516   .2753309     0.68   0.499     -.353387    .7258902
             lag_log_trade |  -.2735897   .1754848    -1.56   0.119    -.6175335    .0703541
      lag_rivalry_thompson |   .5780734   .1092116     5.29   0.000     .3640226    .7921242
        lag_rivalry_shared |  -.1739702   .2192447    -0.79   0.427    -.6036819    .2557416
                lag_troops |  -.0040524   .0030778    -1.32   0.188    -.0100848    .0019799
          adv_signal_last3 |   .1981304   .0666698     2.97   0.003       .06746    .3288007
                     _cons |    1.74199   5.756244     0.30   0.762    -9.540042    13.02402
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1708734   .2808007                     -.7212326    .3794859
---------------------------+----------------------------------------------------------------
                     alpha |   .8429283   .2366948                      .4861526    1.461533
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region i.year lag_log_gdp lag_latency_pilot lag_nwcapability log_distance log_distance_us MID_movingavg
> _notinitiator MID_movingavg_aggressor lag_democracy lag_log_trade lag_rivalry_thompson lag_rivalry_shared lag_troops adv_signal_las
> t3 if sample_atop==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -970.57619  
Iteration 1:   log pseudolikelihood = -830.52711  
Iteration 2:   log pseudolikelihood = -826.35434  
Iteration 3:   log pseudolikelihood =  -826.3088  
Iteration 4:   log pseudolikelihood = -826.29891  
Iteration 5:   log pseudolikelihood = -826.29652  
Iteration 6:   log pseudolikelihood = -826.29601  
Iteration 7:   log pseudolikelihood =  -826.2959  
Iteration 8:   log pseudolikelihood = -826.29588  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -1061.6021  
Iteration 1:   log pseudolikelihood =  -1052.081  
Iteration 2:   log pseudolikelihood = -1007.1802  
Iteration 3:   log pseudolikelihood = -1007.1752  
Iteration 4:   log pseudolikelihood = -1007.1752  

Fitting full model:

Iteration 0:   log pseudolikelihood = -940.91771  (not concave)
Iteration 1:   log pseudolikelihood = -836.89978  
Iteration 2:   log pseudolikelihood =  -812.5738  
Iteration 3:   log pseudolikelihood = -810.15702  
Iteration 4:   log pseudolikelihood = -810.08267  
Iteration 5:   log pseudolikelihood = -810.08264  

Negative binomial regression                    Number of obs     =      1,310
                                                Wald chi2(34)     =          .
Dispersion           = mean                     Prob > chi2       =          .
Log pseudolikelihood = -810.08264               Pseudo R2         =     0.1957

                                                  (Std. Err. adjusted for 36 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.3259093   .3508634    -0.93   0.353    -1.013589    .3617702
                        5  |   2.532322   .5191929     4.88   0.000     1.514722    3.549921
                           |
                      year |
                     1952  |  -1.048535   1.307848    -0.80   0.423     -3.61187      1.5148
                     1953  |  -1.503983   1.117484    -1.35   0.178    -3.694211    .6862445
                     1954  |  -1.064222   .6238909    -1.71   0.088    -2.287025    .1585819
                     1955  |   -.536506   .9582499    -0.56   0.576    -2.414641    1.341629
                     1956  |  -17.36439   .6956477   -24.96   0.000    -18.72783   -16.00094
                     1957  |  -.3862992   1.016488    -0.38   0.704    -2.378578     1.60598
                     1958  |   -.752797   .5399428    -1.39   0.163    -1.811065    .3054715
                     1959  |  -1.879295   1.244736    -1.51   0.131    -4.318933    .5603439
                     1960  |  -.6217468   .5267216    -1.18   0.238    -1.654102    .4106085
                     1961  |  -.4172101   .7789667    -0.54   0.592    -1.943957    1.109537
                     1962  |    .301698   .7708555     0.39   0.696    -1.209151    1.812547
                     1963  |  -1.199548   1.042529    -1.15   0.250    -3.242868     .843772
                     1964  |  -1.281104   .7815723    -1.64   0.101    -2.812958    .2507496
                     1965  |  -.6198193   .5814014    -1.07   0.286    -1.759345    .5197065
                     1966  |  -.3376065    .535359    -0.63   0.528    -1.386891    .7116778
                     1967  |  -.5130478   .7262979    -0.71   0.480    -1.936566      .91047
                     1968  |   -.490277   .8978905    -0.55   0.585     -2.25011    1.269556
                     1969  |   .0872086   .8383558     0.10   0.917    -1.555939    1.730356
                     1970  |  -.2155804   .8413863    -0.26   0.798    -1.864667    1.433506
                     1971  |   .1133486   .7176512     0.16   0.875    -1.293222    1.519919
                     1972  |   .0724384   .7151531     0.10   0.919    -1.329236    1.474113
                     1973  |  -.0926427   .8827937    -0.10   0.916    -1.822887    1.637601
                     1974  |   .2077853   .8181191     0.25   0.800    -1.395699    1.811269
                     1975  |   .4428332   .7288909     0.61   0.543    -.9857667    1.871433
                     1976  |    .635431   .7470815     0.85   0.395    -.8288218    2.099684
                     1977  |    .162854   .9058801     0.18   0.857    -1.612638    1.938346
                     1978  |  -.5176427   .7548967    -0.69   0.493    -1.997213    .9619277
                     1979  |   .8627276   .8793654     0.98   0.327     -.860797    2.586252
                     1980  |   .5272785   .8932713     0.59   0.555    -1.223501    2.278058
                     1981  |   .4518282    .864025     0.52   0.601     -1.24163    2.145286
                     1982  |  -.0112282   .8004185    -0.01   0.989     -1.58002    1.557563
                     1983  |   .4957585   .8001338     0.62   0.536    -1.072475    2.063992
                     1984  |  -.1736734   .9187951    -0.19   0.850    -1.974479    1.627132
                     1985  |   .2064926   .8629749     0.24   0.811    -1.484907    1.897892
                     1986  |  -.3257746   .7944365    -0.41   0.682    -1.882842    1.231292
                     1987  |  -.3751618   .8433852    -0.44   0.656    -2.028166    1.277843
                     1988  |   .0831156   .8670864     0.10   0.924    -1.616343    1.782574
                     1989  |   .3188714   .8097654     0.39   0.694     -1.26824    1.905982
                     1990  |  -.5704864   .9325683    -0.61   0.541    -2.398287    1.257314
                     1991  |   .1425699   1.011243     0.14   0.888     -1.83943     2.12457
                     1992  |  -.0958607   .6297097    -0.15   0.879    -1.330069    1.138348
                     1993  |   .4599787   .6968814     0.66   0.509    -.9058838    1.825841
                     1994  |   .0027504   .8471642     0.00   0.997    -1.657661    1.663162
                     1995  |  -.3181321   .9044607    -0.35   0.725    -2.090843    1.454578
                     1996  |   .5401555   .8341448     0.65   0.517    -1.094738    2.175049
                     1997  |  -1.095559   .9980322    -1.10   0.272    -3.051666    .8605484
                     1998  |  -.0494616   .8575312    -0.06   0.954    -1.730192    1.631269
                     1999  |  -.4358722   .9207792    -0.47   0.636    -2.240566    1.368822
                     2000  |  -1.124406   .9467975    -1.19   0.235    -2.980095    .7312833
                     2001  |   .2601034   .7305826     0.36   0.722    -1.171812    1.692019
                     2002  |  -.0785738   .7077422    -0.11   0.912    -1.465723    1.308575
                     2003  |   .4365139   .6985416     0.62   0.532    -.9326026     1.80563
                     2004  |  -1.431484   1.133874    -1.26   0.207    -3.653835    .7908677
                     2005  |  -.0191628   1.128659    -0.02   0.986    -2.231295    2.192969
                     2006  |  -.4508439   .9133224    -0.49   0.622    -2.240923    1.339235
                     2007  |  -.0672214   .9650918    -0.07   0.944    -1.958766    1.824324
                     2008  |  -.3456078   .7899066    -0.44   0.662    -1.893796    1.202581
                     2009  |   .9607729   .8403591     1.14   0.253    -.6863007    2.607846
                     2010  |   .4888819   .8236983     0.59   0.553    -1.125537    2.103301
                           |
               lag_log_gdp |   .3233267   .1681618     1.92   0.055    -.0062643    .6529178
         lag_latency_pilot |   .8725999   .1759438     4.96   0.000     .5277564    1.217443
          lag_nwcapability |   .9711985   .3570575     2.72   0.007     .2713786    1.671018
              log_distance |  -.3649421   .1863393    -1.96   0.050    -.7301604    .0002762
           log_distance_us |   .3483426   .6699775     0.52   0.603    -.9647892    1.661474
MID_movingavg_notinitiator |   .0318835   .0416019     0.77   0.443    -.0496548    .1134217
   MID_movingavg_aggressor |   .0267396   .0357083     0.75   0.454    -.0432473    .0967266
             lag_democracy |   .1457226   .2809166     0.52   0.604    -.4048637     .696309
             lag_log_trade |  -.2536149   .1909846    -1.33   0.184    -.6279379    .1207081
      lag_rivalry_thompson |    .568571   .1040847     5.46   0.000     .3645688    .7725732
        lag_rivalry_shared |  -.1946651   .2431294    -0.80   0.423      -.67119    .2818599
                lag_troops |  -.0035156   .0028274    -1.24   0.214    -.0090573     .002026
          adv_signal_last3 |   .2028007   .0880989     2.30   0.021     .0301301    .3754713
                     _cons |  -5.832641    5.70446    -1.02   0.307    -17.01318    5.347894
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.5797584   .5420822                      -1.64222    .4827033
---------------------------+----------------------------------------------------------------
                     alpha |   .5600337   .3035843                      .1935499    1.620449
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.ccode postcw t t2 t3 log_cas us_gdp_growth lag_latency_pilot lag_nwcapability MID_movingavg_notinitiato
> r MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy lag_troops adv_signal_last3   if sample_ato
> p==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood =  -1601.329  
Iteration 1:   log pseudolikelihood = -1197.0541  
Iteration 2:   log pseudolikelihood = -852.61083  
Iteration 3:   log pseudolikelihood = -843.97962  
Iteration 4:   log pseudolikelihood = -843.70163  
Iteration 5:   log pseudolikelihood =  -843.6936  
Iteration 6:   log pseudolikelihood =  -843.6918  
Iteration 7:   log pseudolikelihood =  -843.6914  
Iteration 8:   log pseudolikelihood = -843.69134  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -1062.8848  
Iteration 1:   log pseudolikelihood = -1055.1371  
Iteration 2:   log pseudolikelihood = -1008.1073  
Iteration 3:   log pseudolikelihood = -1008.1049  
Iteration 4:   log pseudolikelihood = -1008.1049  

Fitting full model:

Iteration 0:   log pseudolikelihood = -1008.1049  (not concave)
Iteration 1:   log pseudolikelihood = -838.64907  
Iteration 2:   log pseudolikelihood = -815.15594  
Iteration 3:   log pseudolikelihood = -812.41784  
Iteration 4:   log pseudolikelihood = -812.28931  
Iteration 5:   log pseudolikelihood = -812.25844  
Iteration 6:   log pseudolikelihood = -812.25223  
Iteration 7:   log pseudolikelihood = -812.25091  
Iteration 8:   log pseudolikelihood =  -812.2506  
Iteration 9:   log pseudolikelihood = -812.25053  
Iteration 10:  log pseudolikelihood = -812.25052  

Negative binomial regression                    Number of obs     =      1,314
                                                Wald chi2(34)     =          .
Dispersion           = mean                     Prob > chi2       =          .
Log pseudolikelihood = -812.25052               Pseudo R2         =     0.1943

                                                  (Std. Err. adjusted for 36 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                     ccode |
                      210  |  -.1596188   .2767309    -0.58   0.564    -.7020013    .3827637
                      211  |  -.2539213   .3363456    -0.75   0.450    -.9131466     .405304
                      212  |  -15.91464   1.087866   -14.63   0.000    -18.04682   -13.78247
                      220  |   .3519483   .1239357     2.84   0.005     .1090388    .5948578
                      230  |  -1.471893   .3866964    -3.81   0.000    -2.229804   -.7139814
                      235  |  -.1652716   .3735798    -0.44   0.658    -.8974745    .5669313
                      255  |   .2789921    .981277     0.28   0.776    -1.644276     2.20226
                      290  |   2.011494   .4356101     4.62   0.000     1.157714    2.865274
                      310  |  -.1485553   .4300259    -0.35   0.730    -.9913906    .6942799
                      316  |   .5342472   .4303253     1.24   0.214    -.3091749    1.377669
                      317  |  -15.93868   1.097358   -14.52   0.000    -18.08946   -13.78789
                      325  |   -.043503   .2400332    -0.18   0.856    -.5139594    .4269533
                      339  |    -16.127   1.107494   -14.56   0.000    -18.29765   -13.95635
                      344  |  -16.10004   1.102208   -14.61   0.000    -18.26033   -13.93975
                      349  |  -15.96226    1.10076   -14.50   0.000    -18.11971   -13.80481
                      350  |   1.002115   .4479064     2.24   0.025     .1242344    1.879995
                      355  |   1.413502   .4334086     3.26   0.001     .5640363    2.262967
                      360  |    .347536   .4211206     0.83   0.409    -.4778452    1.172917
                      366  |  -15.95727   1.099628   -14.51   0.000     -18.1125   -13.80204
                      367  |   1.118152   .4298634     2.60   0.009     .2756356    1.960669
                      368  |   1.507657   .4255248     3.54   0.000     .6736435     2.34167
                      385  |  -.7519948   .3515355    -2.14   0.032    -1.440992   -.0629979
                      390  |   -.145338     .39258    -0.37   0.711    -.9147806    .6241046
                      395  |  -1.744893   .3688974    -4.73   0.000    -2.467918   -1.021867
                      630  |   .8008937   .4712301     1.70   0.089    -.1227003    1.724488
                      640  |   .7216998   .3663166     1.97   0.049     .0037325    1.439667
                      666  |   1.671672   .1870956     8.93   0.000     1.304971    2.038373
                      713  |   2.109313   .4383769     4.81   0.000      1.25011    2.968516
                      732  |   2.013666   .4448288     4.53   0.000     1.141817    2.885514
                      740  |   2.680695   .3128441     8.57   0.000     2.067532    3.293858
                      770  |   .7438697   .2163544     3.44   0.001     .3198228    1.167917
                      800  |   1.813781   .5284575     3.43   0.001      .778023    2.849538
                      840  |    1.79753   .3996315     4.50   0.000     1.014267    2.580794
                      900  |   1.639012   .4316218     3.80   0.000     .7930491    2.484975
                      920  |   1.908546   .3824262     4.99   0.000     1.159005    2.658088
                           |
                    postcw |   .4372214   .4713987     0.93   0.354    -.4867031    1.361146
                         t |  -.1739257   .0973327    -1.79   0.074    -.3646942    .0168428
                        t2 |   .0031587   .0026315     1.20   0.230     -.001999    .0083164
                        t3 |  -.0000208   .0000249    -0.83   0.404    -.0000696     .000028
                   log_cas |   .0520996   .0305801     1.70   0.088    -.0078363    .1120355
             us_gdp_growth |  -.0442679    .022093    -2.00   0.045    -.0875693   -.0009665
         lag_latency_pilot |   .5617926   .2862675     1.96   0.050     .0007185    1.122867
          lag_nwcapability |   .8494415    .419304     2.03   0.043     .0276207    1.671262
MID_movingavg_notinitiator |   .0462386   .0432957     1.07   0.286    -.0386194    .1310967
   MID_movingavg_aggressor |   .0331532    .029507     1.12   0.261    -.0246794    .0909859
        lag_adversary_cinc |   .0237635   .0180407     1.32   0.188    -.0115955    .0591225
               lag_us_cinc |   -.266328   .0706882    -3.77   0.000    -.4048743   -.1277816
          provocation_new3 |   .2149642   .1614846     1.33   0.183    -.1015397    .5314682
             lag_democracy |   .1560048    .279142     0.56   0.576    -.3911034    .7031131
                lag_troops |  -.0042946   .0068317    -0.63   0.530    -.0176845    .0090953
          adv_signal_last3 |   .0803538   .0837566     0.96   0.337    -.0838061    .2445138
                     _cons |    4.08264   2.231386     1.83   0.067    -.2907962    8.456076
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.3595894   .2691349                     -.8870842    .1679054
---------------------------+----------------------------------------------------------------
                     alpha |   .6979628   .1878462                      .4118549    1.182825
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson lag_idealpoint_us_diff lag_rivalry_shared lag_troops adv_signal_last3 if sample_atop==1, vce(clus
> ter id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -986.45289  
Iteration 1:   log pseudolikelihood =  -793.5122  
Iteration 2:   log pseudolikelihood = -722.43763  
Iteration 3:   log pseudolikelihood = -721.36377  
Iteration 4:   log pseudolikelihood = -721.35988  
Iteration 5:   log pseudolikelihood = -721.35988  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood =  -889.8324  
Iteration 1:   log pseudolikelihood = -840.81197  
Iteration 2:   log pseudolikelihood = -840.78547  
Iteration 3:   log pseudolikelihood = -840.78547  

Fitting full model:

Iteration 0:   log pseudolikelihood = -766.64038  
Iteration 1:   log pseudolikelihood = -710.60052  
Iteration 2:   log pseudolikelihood = -692.48078  
Iteration 3:   log pseudolikelihood = -690.25217  
Iteration 4:   log pseudolikelihood = -690.24807  
Iteration 5:   log pseudolikelihood = -690.24807  

Negative binomial regression                    Number of obs     =      1,126
                                                Wald chi2(25)     =   13792.85
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -690.24807               Pseudo R2         =     0.1790

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |  -.2374257   .2964462    -0.80   0.423    -.8184496    .3435983
                        5  |   3.524758   .5045305     6.99   0.000     2.535896     4.51362
                           |
                    postcw |   .4684991   .4683017     1.00   0.317    -.4493553    1.386354
                         t |   -.380767   .1531129    -2.49   0.013    -.6808628   -.0806713
                        t2 |   .0094952   .0041261     2.30   0.021     .0014083    .0175822
                        t3 |  -.0000799   .0000369    -2.17   0.030    -.0001521   -7.63e-06
                   log_cas |   .1033117   .0345292     2.99   0.003     .0356357    .1709877
             us_gdp_growth |  -.0713186   .0264655    -2.69   0.007    -.1231899   -.0194472
               lag_log_gdp |   .6412281   .1984438     3.23   0.001     .2522854    1.030171
         lag_latency_pilot |   1.148921   .2087864     5.50   0.000     .7397067    1.558134
          lag_nwcapability |   1.218395   .2895124     4.21   0.000     .6509613    1.785829
              log_distance |  -.6275539   .1692417    -3.71   0.000    -.9592616   -.2958461
           log_distance_us |   .2682667   .8132854     0.33   0.742    -1.325743    1.862277
MID_movingavg_notinitiator |  -.0139507   .0475819    -0.29   0.769    -.1072095     .079308
   MID_movingavg_aggressor |  -.0020404   .0307243    -0.07   0.947    -.0622589    .0581781
        lag_adversary_cinc |  -.0264286   .0263638    -1.00   0.316    -.0781007    .0252435
               lag_us_cinc |  -.3723055   .1114589    -3.34   0.001    -.5907609   -.1538501
          provocation_new3 |   .1294787   .2067433     0.63   0.531    -.2757308    .5346882
             lag_democracy |   .0446995   .3484435     0.13   0.898    -.6382373    .7276363
             lag_log_trade |  -.6055181   .1765988    -3.43   0.001    -.9516454   -.2593907
      lag_rivalry_thompson |   .6202689    .128562     4.82   0.000      .368292    .8722457
    lag_idealpoint_us_diff |   .3712224   .1713929     2.17   0.030     .0352984    .7071463
        lag_rivalry_shared |  -.3732635   .2456641    -1.52   0.129    -.8547562    .1082293
                lag_troops |  -.0092631   .0017992    -5.15   0.000    -.0127894   -.0057368
          adv_signal_last3 |   .1817138   .0546423     3.33   0.001     .0746169    .2888108
                     _cons |   6.156701   9.029232     0.68   0.495    -11.54027    23.85367
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1975454   .2758743                     -.7382491    .3431583
---------------------------+----------------------------------------------------------------
                     alpha |   .8207429   .2264219                        .47795    1.409392
--------------------------------------------------------------------------------------------

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson lag_rivalry_shared lag_troops adv_signal_last3 if sample_atop_americas==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1952.7805  
Iteration 1:   log pseudolikelihood = -1487.2143  
Iteration 2:   log pseudolikelihood = -1135.8369  
Iteration 3:   log pseudolikelihood = -977.79776  
Iteration 4:   log pseudolikelihood = -972.80809  
Iteration 5:   log pseudolikelihood = -972.76265  
Iteration 6:   log pseudolikelihood = -972.76264  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -1457.4788  (not concave)
Iteration 1:   log pseudolikelihood = -1291.8846  
Iteration 2:   log pseudolikelihood = -1291.8749  
Iteration 3:   log pseudolikelihood = -1291.8749  

Fitting full model:

Iteration 0:   log pseudolikelihood = -1189.7664  (not concave)
Iteration 1:   log pseudolikelihood = -1022.4183  
Iteration 2:   log pseudolikelihood = -949.87421  
Iteration 3:   log pseudolikelihood =  -934.1441  
Iteration 4:   log pseudolikelihood = -931.17616  
Iteration 5:   log pseudolikelihood = -931.11813  
Iteration 6:   log pseudolikelihood =  -931.1181  

Negative binomial regression                    Number of obs     =      2,933
                                                Wald chi2(25)     =    1765.78
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood =  -931.1181               Pseudo R2         =     0.2793

                                                  (Std. Err. adjusted for 70 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        2  |   3.000643   .7013099     4.28   0.000     1.626101    4.375185
                        4  |   3.397597   .8108141     4.19   0.000      1.80843    4.986763
                        5  |   6.664544   .7977407     8.35   0.000     5.101001    8.228087
                           |
                    postcw |  -.0123929   .4822909    -0.03   0.979    -.9576657    .9328799
                         t |  -.2136605   .0808329    -2.64   0.008    -.3720901   -.0552309
                        t2 |   .0043153   .0021443     2.01   0.044     .0001125    .0085181
                        t3 |  -.0000298   .0000203    -1.47   0.142    -.0000696    9.98e-06
                   log_cas |   .0550223   .0281081     1.96   0.050    -.0000686    .1101133
             us_gdp_growth |  -.0517634   .0204317    -2.53   0.011    -.0918088   -.0117179
               lag_log_gdp |   .2285923   .1016672     2.25   0.025     .0293283    .4278563
         lag_latency_pilot |   .7348478    .147286     4.99   0.000     .4461726    1.023523
          lag_nwcapability |   .6258068   .3463012     1.81   0.071    -.0529312    1.304545
              log_distance |  -.1565147   .1697217    -0.92   0.356    -.4891631    .1761337
           log_distance_us |   -1.63151    .347277    -4.70   0.000    -2.312161   -.9508597
MID_movingavg_notinitiator |   .0500755   .0403185     1.24   0.214    -.0289472    .1290983
   MID_movingavg_aggressor |   .0097106   .0308398     0.31   0.753    -.0507343    .0701555
        lag_adversary_cinc |  -.0166899   .0211345    -0.79   0.430    -.0581127    .0247329
               lag_us_cinc |  -.2497352    .069183    -3.61   0.000    -.3853314   -.1141389
          provocation_new3 |   .2453538   .1522223     1.61   0.107    -.0529965     .543704
             lag_democracy |   .0991819   .2279997     0.44   0.664    -.3476893     .546053
             lag_log_trade |  -.1204021   .0518264    -2.32   0.020    -.2219799   -.0188243
      lag_rivalry_thompson |   .6181421   .1546547     4.00   0.000     .3150246    .9212597
        lag_rivalry_shared |   -.221433    .173144    -1.28   0.201     -.560789     .117923
                lag_troops |  -.0051811   .0032878    -1.58   0.115    -.0116252    .0012629
          adv_signal_last3 |   .2202195   .0765434     2.88   0.004     .0701972    .3702418
                     _cons |   13.91826   3.384462     4.11   0.000      7.28484    20.55169
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.0617192   .3125803                     -.6743653    .5509268
---------------------------+----------------------------------------------------------------
                     alpha |   .9401468   .2938713                      .5094797     1.73486
--------------------------------------------------------------------------------------------

. 
. 
. 
. *Figure A1
. bys year: egen annual_statements = mean(statements_americas) if sample_cow==1
(10,148 missing values generated)

. label var annual_statements "Average Statements per Ally"

. preserve

. keep if country=="France"
(11,345 observations deleted)

. graph twoway (line annual_statements year if year < 2011, connect(l) lwidth(thick) clpattern(solid)), ylabel(0(0.5)2) xlabel(1950(1
> 0)2010) xtick(1950(5)2010) graphregion(fcolor(white)) xtitle("Year") title("Average U.S. Statements")

. restore

. 
. 
. eststo clear

. *Generating coefficients and standard errors for Figure 1*
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(log_cas=(0 2.397895 4.615120 6.908754 9.210440 9.903537)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1294322  _b[1bn._at]
          2  |    .156374  _b[2._at]
          3  |   .1862513  _b[3._at]
          4  |   .2231779  _b[4._at]
          5  |   .2675953  _b[5._at]
          6  |   .2826282  _b[6._at]
------------------------------------------------------------------------------

. 
. preserve

. gen order = _n

. gen coef = .
(11,406 missing values generated)

. gen se = .
(11,406 missing values generated)

. replace coef = _b[1bn._at] if order==1
(1 real change made)

. replace coef = _b[2._at] if order==2
(1 real change made)

. replace coef = _b[3._at] if order==3
(1 real change made)

. replace coef = _b[4._at] if order==4
(1 real change made)

. replace coef = _b[5._at] if order==5
(1 real change made)

. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(log_cas=(0 2.397895 4.615120 6.908754 9.210440 9.903537)) atmeans post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

1._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =           0
               us_gdp_gro~h    =    3.078518 (mean)
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

2._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    2.397895
               us_gdp_gro~h    =    3.078518 (mean)
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

3._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =     4.61512
               us_gdp_gro~h    =    3.078518 (mean)
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

4._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    6.908754
               us_gdp_gro~h    =    3.078518 (mean)
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

5._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =     9.21044
               us_gdp_gro~h    =    3.078518 (mean)
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

6._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    9.903537
               us_gdp_gro~h    =    3.078518 (mean)
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1294322  _b[1bn._at]
          2  |    .156374  _b[2._at]
          3  |   .1862513  _b[3._at]
          4  |   .2231779  _b[4._at]
          5  |   .2675953  _b[5._at]
          6  |   .2826282  _b[6._at]
------------------------------------------------------------------------------

. 
. matrix rV = r(V)

. replace se = sqrt(rV[1,1]) if order==1
(1 real change made)

. replace se = sqrt(rV[2,2]) if order==2
(1 real change made)

. replace se = sqrt(rV[3,3]) if order==3
(1 real change made)

. replace se = sqrt(rV[4,4]) if order==4
(1 real change made)

. replace se = sqrt(rV[5,5]) if order==5
(1 real change made)

. keep if coef != . & se != .
(11,401 observations deleted)

. keep order coef se

. save statements_coef1.dta, replace
(note: file statements_coef1.dta not found)
file statements_coef1.dta saved

. restore

. 
. 
. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(us_gdp_growth=(-1(1)5)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .2192399  _b[1bn._at]
          2  |   .2063486  _b[2._at]
          3  |   .1942154  _b[3._at]
          4  |   .1827956  _b[4._at]
          5  |   .1720473  _b[5._at]
          6  |   .1619309  _b[6._at]
          7  |   .1524094  _b[7._at]
------------------------------------------------------------------------------

. preserve

. gen order = _n

. gen coef = .
(11,406 missing values generated)

. gen se = .
(11,406 missing values generated)

. replace coef = _b[1bn._at] if order==1
(1 real change made)

. replace coef = _b[2._at] if order==2
(1 real change made)

. replace coef = _b[3._at] if order==3
(1 real change made)

. replace coef = _b[4._at] if order==4
(1 real change made)

. replace coef = _b[5._at] if order==5
(1 real change made)

. replace coef = _b[6._at] if order==6
(1 real change made)

. replace coef = _b[7._at] if order==7
(1 real change made)

. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(us_gdp_growth=(-1(1)5)) atmeans post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

1._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =          -1
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

2._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =           0
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

3._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =           1
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

4._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =           2
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

5._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =           3
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

6._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =           4
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

7._at        : 2.region        =     .670418 (mean)
               4.region        =    .0900322 (mean)
               5.region        =    .2395498 (mean)
               postcw          =     .392283 (mean)
               t               =    32.42444 (mean)
               t2              =    1365.217 (mean)
               t3              =    64222.33 (mean)
               log_cas         =    3.548826 (mean)
               us_gdp_gro~h    =           5
               lag_log_gdp     =     25.8148 (mean)
               lag_latenc~t    =    .1446945 (mean)
               lag_nwcapa~y    =    .1053055 (mean)
               log_distance    =    7.575206 (mean)
               log_distan~s    =    8.971838 (mean)
               MID_movi~tor    =    1.431672 (mean)
               MID_movi~sor    =    1.128617 (mean)
               lag_advers~c    =    13.35931 (mean)
               lag_us_cinc     =    17.40447 (mean)
               provocatio~3    =    .3480707 (mean)
               lag_democr~y    =    .8713826 (mean)
               lag_log_tr~e    =    22.32744 (mean)
               lag_rivalr~n    =    .3078778 (mean)
               lag_rivalr~d    =    .1149518 (mean)
               lag_troops      =    17.70944 (mean)
               adv_signal~3    =    .4011254 (mean)

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .2192399  _b[1bn._at]
          2  |   .2063486  _b[2._at]
          3  |   .1942154  _b[3._at]
          4  |   .1827956  _b[4._at]
          5  |   .1720473  _b[5._at]
          6  |   .1619309  _b[6._at]
          7  |   .1524094  _b[7._at]
------------------------------------------------------------------------------

. 
. matrix rV = r(V)

. replace se = sqrt(rV[1,1]) if order==1
(1 real change made)

. replace se = sqrt(rV[2,2]) if order==2
(1 real change made)

. replace se = sqrt(rV[3,3]) if order==3
(1 real change made)

. replace se = sqrt(rV[4,4]) if order==4
(1 real change made)

. replace se = sqrt(rV[5,5]) if order==5
(1 real change made)

. replace se = sqrt(rV[6,6]) if order==6
(1 real change made)

. replace se = sqrt(rV[7,7]) if order==7
(1 real change made)

. keep if coef != . & se != .
(11,399 observations deleted)

. keep order coef se

. save statements_coef2.dta, replace
(note: file statements_coef2.dta not found)
file statements_coef2.dta saved

. restore

. 
. 
. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(lag_log_gdp=(23.025850 25.328436 27.631021)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .0341695  _b[1bn._at]
          2  |   .1292764  _b[2._at]
          3  |   .4891024  _b[3._at]
------------------------------------------------------------------------------

. preserve

. gen order = _n

. gen coef = .
(11,406 missing values generated)

. gen se = .
(11,406 missing values generated)

. replace coef = _b[1bn._at] if order==1
(1 real change made)

. replace coef = _b[2._at] if order==2
(1 real change made)

. replace coef = _b[3._at] if order==3
(1 real change made)

. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(lag_log_gdp=(23.025850 25.328436 27.631021)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .0341695  _b[1bn._at]
          2  |   .1292764  _b[2._at]
          3  |   .4891024  _b[3._at]
------------------------------------------------------------------------------

. matrix rV = r(V)

. replace se = sqrt(rV[1,1]) if order==1
(1 real change made)

. replace se = sqrt(rV[2,2]) if order==2
(1 real change made)

. replace se = sqrt(rV[3,3]) if order==3
(1 real change made)

. keep if coef != . & se != .
(11,403 observations deleted)

. keep order coef se

. save statements_coef3.dta, replace
(note: file statements_coef3.dta not found)
file statements_coef3.dta saved

. restore

. 
. 
. 
. 
. 
. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(lag_latency_pilot=(0(1)1)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1498038  _b[1bn._at]
          2  |   .3773732  _b[2._at]
------------------------------------------------------------------------------

. preserve

. gen order = _n

. gen coef = .
(11,406 missing values generated)

. gen se = .
(11,406 missing values generated)

. replace coef = _b[1bn._at] if order==1
(1 real change made)

. replace coef = _b[2._at] if order==2
(1 real change made)

. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(lag_latency_pilot=(0(1)1)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1498038  _b[1bn._at]
          2  |   .3773732  _b[2._at]
------------------------------------------------------------------------------

. matrix rV = r(V)

. replace se = sqrt(rV[1,1]) if order==1
(1 real change made)

. replace se = sqrt(rV[2,2]) if order==2
(1 real change made)

. keep if coef != . & se != .
(11,404 observations deleted)

. keep order coef se

. save statements_coef4.dta, replace
(note: file statements_coef4.dta not found)
file statements_coef4.dta saved

. restore

. 
. 
. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(lag_nwcapability=(0(1)1)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1533988  _b[1bn._at]
          2  |   .4358654  _b[2._at]
------------------------------------------------------------------------------

. preserve

. gen order = _n

. gen coef = .
(11,406 missing values generated)

. gen se = .
(11,406 missing values generated)

. replace coef = _b[1bn._at] if order==1
(1 real change made)

. replace coef = _b[2._at] if order==2
(1 real change made)

. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(lag_nwcapability=(0(1)1)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1533988  _b[1bn._at]
          2  |   .4358654  _b[2._at]
------------------------------------------------------------------------------

. matrix rV = r(V)

. replace se = sqrt(rV[1,1]) if order==1
(1 real change made)

. replace se = sqrt(rV[2,2]) if order==2
(1 real change made)

. keep if coef != . & se != .
(11,404 observations deleted)

. keep order coef se

. save statements_coef5.dta, replace
(note: file statements_coef5.dta not found)
file statements_coef5.dta saved

. restore

. 
. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(adv_signal_last3=(0(1)3)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1602591  _b[1bn._at]
          2  |   .1890243  _b[2._at]
          3  |   .2229525  _b[3._at]
          4  |   .2629706  _b[4._at]
------------------------------------------------------------------------------

. preserve

. gen order = _n

. gen coef = .
(11,406 missing values generated)

. gen se = .
(11,406 missing values generated)

. replace coef = _b[1bn._at] if order==1
(1 real change made)

. replace coef = _b[2._at] if order==2
(1 real change made)

. replace coef = _b[3._at] if order==3
(1 real change made)

. replace coef = _b[4._at] if order==4
(1 real change made)

. 
. nbreg statements_americas i.region postcw t t2 t3 log_cas us_gdp_growth lag_log_gdp lag_latency_pilot lag_nwcapability log_distance
>  log_distance_us MID_movingavg_notinitiator MID_movingavg_aggressor lag_adversary_cinc lag_us_cinc provocation_new3 lag_democracy l
> ag_log_trade lag_rivalry_thompson  lag_rivalry_shared lag_troops adv_signal_last3 if sample_cow==1, vce(cluster id)

Fitting Poisson model:

Iteration 0:   log pseudolikelihood = -1055.3127  
Iteration 1:   log pseudolikelihood = -865.09062  
Iteration 2:   log pseudolikelihood = -811.36191  
Iteration 3:   log pseudolikelihood = -810.14769  
Iteration 4:   log pseudolikelihood =  -810.1436  
Iteration 5:   log pseudolikelihood =  -810.1436  

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = -980.61832  
Iteration 1:   log pseudolikelihood = -929.80463  
Iteration 2:   log pseudolikelihood = -929.67092  
Iteration 3:   log pseudolikelihood =  -929.6709  

Fitting full model:

Iteration 0:   log pseudolikelihood = -849.90032  
Iteration 1:   log pseudolikelihood = -786.83139  
Iteration 2:   log pseudolikelihood = -772.98326  
Iteration 3:   log pseudolikelihood = -772.48697  
Iteration 4:   log pseudolikelihood = -772.48547  
Iteration 5:   log pseudolikelihood = -772.48547  

Negative binomial regression                    Number of obs     =      1,244
                                                Wald chi2(24)     =    3002.76
Dispersion           = mean                     Prob > chi2       =     0.0000
Log pseudolikelihood = -772.48547               Pseudo R2         =     0.1691

                                                  (Std. Err. adjusted for 33 clusters in id)
--------------------------------------------------------------------------------------------
                           |               Robust
       statements_americas |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    region |
                        4  |   -.489248   .2520313    -1.94   0.052    -.9832203    .0047242
                        5  |   3.045549   .4505294     6.76   0.000     2.162528    3.928571
                           |
                    postcw |   .1874806   .4575411     0.41   0.682    -.7092834    1.084245
                         t |  -.3099749   .0864215    -3.59   0.000    -.4793579    -.140592
                        t2 |    .006562    .002436     2.69   0.007     .0017875    .0113366
                        t3 |  -.0000486    .000024    -2.03   0.043    -.0000957   -1.61e-06
                   log_cas |   .0788582   .0309359     2.55   0.011     .0182251    .1394914
             us_gdp_growth |  -.0605993    .023443    -2.58   0.010    -.1065467   -.0146519
               lag_log_gdp |   .5778804   .1978244     2.92   0.003     .1901516    .9656092
         lag_latency_pilot |   .9239081   .1663799     5.55   0.000     .5978095    1.250007
          lag_nwcapability |   1.044292   .3253234     3.21   0.001       .40667    1.681914
              log_distance |  -.4179051   .1741582    -2.40   0.016     -.759249   -.0765612
           log_distance_us |   .1361485   .5439276     0.25   0.802    -.9299301    1.202227
MID_movingavg_notinitiator |   .0043977   .0387223     0.11   0.910    -.0714966    .0802919
   MID_movingavg_aggressor |   .0255337   .0270959     0.94   0.346    -.0275732    .0786407
        lag_adversary_cinc |   -.031439   .0220168    -1.43   0.153     -.074591    .0117131
               lag_us_cinc |  -.3437343   .0729811    -4.71   0.000    -.4867746    -.200694
          provocation_new3 |   .1543866   .1838646     0.84   0.401    -.2059814    .5147545
             lag_democracy |   .1253958   .3537991     0.35   0.723    -.5680377    .8188293
             lag_log_trade |  -.4839543   .1890977    -2.56   0.010     -.854579   -.1133297
      lag_rivalry_thompson |   .5396608   .1210004     4.46   0.000     .3025044    .7768172
        lag_rivalry_shared |  -.1653962   .2313345    -0.71   0.475    -.6188034     .288011
                lag_troops |  -.0043163   .0030593    -1.41   0.158    -.0103125    .0016798
          adv_signal_last3 |   .1650835    .062406     2.65   0.008     .0427701     .287397
                     _cons |   5.254101   5.189282     1.01   0.311    -4.916705    15.42491
---------------------------+----------------------------------------------------------------
                  /lnalpha |  -.1153175   .2918823                     -.6873962    .4567613
---------------------------+----------------------------------------------------------------
                     alpha |   .8910832   .2600914                      .5028838    1.578952
--------------------------------------------------------------------------------------------

. margins, at(adv_signal_last3=(0(1)3)) atmeans noatlegend post coeflegend

Adjusted predictions                            Number of obs     =      1,244
Model VCE    : Robust

Expression   : Predicted number of events, predict()

------------------------------------------------------------------------------
             |     Margin  Legend
-------------+----------------------------------------------------------------
         _at |
          1  |   .1602591  _b[1bn._at]
          2  |   .1890243  _b[2._at]
          3  |   .2229525  _b[3._at]
          4  |   .2629706  _b[4._at]
------------------------------------------------------------------------------

. matrix rV = r(V)

. replace se = sqrt(rV[1,1]) if order==1
(1 real change made)

. replace se = sqrt(rV[2,2]) if order==2
(1 real change made)

. replace se = sqrt(rV[3,3]) if order==3
(1 real change made)

. replace se = sqrt(rV[4,4]) if order==4
(1 real change made)

. keep if coef != . & se != .
(11,402 observations deleted)

. keep order coef se

. save statements_coef6.dta, replace
(note: file statements_coef6.dta not found)
file statements_coef6.dta saved

. restore

. 
. 
end of do-file

. log close
